Editor's Note: Sensors, as the "nerve endings of the information age," have permeated every critical field of the socio-economic landscape. Since October 2025, China Electronics News has invited Guo Yuansheng, Deputy Director of the Science and Technology Committee of the Central Committee of the Jiusan Society and Executive Vice Chairman of the China Sensor and IoT (Internet of Things) Industry Alliance, to launch the column "Guo Yuansheng Explains Sensors." Focusing on eight major fields and scenarios: power, major equipment, intelligent manufacturing, smart agriculture, smart healthcare and big health, smart home appliances and consumer electronics, urban security, and low-altitude economy, it has sequentially published articles such as "Stationed on the Power Generation Side, Sensors Become the Cornerstone of Stable Operation in New Power Systems" and "Energy Storage Sensors Clarify Three Core Development Directions," which have attracted widespread attention and received overwhelming praise from readers. This publication is the fourth article in the consumer electronics field, focusing on wearable sensors, elaborating on their application prospects, industrial status quo, and future recommendations to build industrial consensus and promote industrial development.
Given the deep evolution of the global scientific and technological revolution and industrial transformation, and the establishment of the strategic goals of China's "15th Five-Year Plan," wearable sensors, as the core hub connecting the physical world and digital intelligence, are becoming a key support for practicing the Healthy China strategy and promoting the intelligent upgrading of industries with their technical characteristics of miniaturization, low power consumption, and high integration. Their dual characteristics of livelihood attributes and industrial value not only reshape the paradigm of personal health management but also deeply integrate into multiple fields and scenarios such as industrial safety protection and public service optimization, driving systematic changes in lifestyles and production modes.
As the concept of proactive health becomes popular and the digital transformation of the manufacturing industry accelerates, traditional monitoring methods can no longer meet the diverse needs for real-time, precise, and scenario-based monitoring. The market pursues more precise state perception and longer battery life; the medical field urgently needs to break through the bottlenecks of non-invasive detection and real-time intervention; and industrial and special scenarios impose strict requirements on protection levels and anti-interference capabilities. These differentiated needs are becoming the core driving force for the technological innovation of wearable sensors. Relying on the technical advantages of miniaturization, low power consumption, and multi-parameter monitoring, wearable sensors can precisely match various needs. They can not only provide individuals with 24/7 health data tracking to promote the popularization of proactive health management concepts but also build a "human-machine-environment" collaborative monitoring system for industrial scenarios, achieving a dual improvement in production safety and efficiency. This deep coupling of technology and demand not only accelerates iterative innovation in sensitive mechanisms, material selection, and structural design but also drives their application in multiple fields from "single-point trials" to "systematic penetration," becoming a key link connecting livelihood improvement and industrial upgrading.
I. Sensitive Mechanisms and Materials Driven by User Needs
Consumer-Grade Wearable Sensors: Comfort and Low Power Consumption as Core Needs
Consumer-grade wearable devices mainly target scenarios such as daily health monitoring and sports recording. They have high requirements for wearing comfort, battery life, and cost sensitivity. Therefore, sensors need to feature flexibility, low power consumption, and miniaturization. Most adopt capacitive, resistive, or photoelectric sensitive mechanisms. For example, the heart rate sensor in smart bracelets uses green LED light to illuminate the skin, detects changes in light intensity caused by blood flow, and then converts it into heart rate data through algorithms; step counting relies on capacitive accelerometers, which determine the user's motion state by sensing acceleration changes in three-dimensional space.
In terms of material selection, a balance between performance and cost is required. Flexible substrates mostly use polymer materials such as polydimethylsiloxane (PDMS) and polyimide (PI), which have good flexibility and biocompatibility, can fit snugly against the skin, and have low costs suitable for large-scale mass production. Heart rate sensors commonly use silicon-based photodiodes, while accelerometers use silicon-based capacitive structures prepared by MEMS (Micro-Electro-Mechanical Systems) processes, which can meet miniaturization needs and control power consumption to the microwatt level, ensuring device battery life of 7-14 days.
Medical-Grade Wearable Sensors: High Precision and Biocompatibility as Core Needs
Medical-grade wearable devices are mainly used in scenarios such as chronic disease management and postoperative monitoring. They need to meet clinical-grade detection accuracy, and long-term wearing must not cause skin allergies or tissue damage. Therefore, high precision, high stability, and biocompatibility are core requirements. The detection principles vary significantly across different medical scenarios: Continuous Glucose Monitoring (CGM) sensors mostly adopt the enzyme biosensing principle. Glucose oxidase fixed on the electrode surface reacts with glucose in the blood. The intensity of the generated electrical signal is proportional to the glucose concentration, and the detection accuracy needs to be controlled within ±15% (complying with the international ISO 15197 standard). Non-invasive blood pressure monitoring sensors are based on the oscillometric method, detecting oscillation waves of pressure inside the cuff through pressure sensors, and calculating systolic and diastolic blood pressure combined with algorithms, requiring the measurement error to be no more than ±5mmHg.
Material selection has strict requirements for biocompatibility. Substrate materials need to use medical-grade silicone rubber, polylactic acid (PLA), etc., certified for biocompatibility to avoid skin irritation. For sensitive components, the working electrodes of CGM sensors often use precious metals such as gold and platinum, with surfaces modified with nano-scale carbon materials (such as carbon nanotubes and graphene) to improve electron conduction efficiency, while being wrapped in biocompatible film layers (such as polyethylene glycol) to prevent enzyme activity reduction. The pressure-sensitive units of non-invasive blood pressure sensors mostly use silicon-based piezoresistive MEMS structures, paired with medical-grade polyurethane cuff materials to ensure long-term stability. In addition, medical sensors also need anti-interference capabilities, such as reducing the impact of electromagnetic interference on detection signals through shielding layer design, ensuring detection accuracy in complex electromagnetic environments in hospitals.
Industrial and Special Wearable Sensors: Extreme Environment Tolerance and High Reliability as Core Needs
Industrial and special scenarios have the most stringent requirements for wearable sensors. They need to work stably in extreme environments such as high temperature, low temperature, humidity, dust, and strong vibration, while possessing characteristics like fast response, anti-interference, and corrosion resistance to ensure the safety of industrial personnel and the execution of special tasks. From the perspective of sensitive mechanisms, the sensing principles for different scenarios are highly targeted: Gas sensors in industrial smart safety helmets adopt catalytic combustion or electrochemical principles. When detecting combustible gases (such as methane) or toxic gases (such as carbon monoxide), the catalyst on the sensor surface reacts, producing changes in electrical signals, and the alarm response needs to be completed within 30 seconds (complying with GB/T 50493-2019 "Design Standard for Detection and Alarm of Combustible and Toxic Gases in Petrochemical Industry"). Impact sensors in special smart bulletproof vests are based on the piezoelectric principle, using the charge signal generated by piezoelectric ceramics (such as PZT) when impacted to quickly determine the impact location and intensity, with a response time of less than 5ms to ensure the timely activation of subsequent protection mechanisms.
In terms of material selection, industrial and special sensors need to prioritize environmental adaptability. Substrate materials mostly use engineering plastics (such as polyether ether ketone PEEK) or metal alloys (such as stainless steel 316L) that are resistant to high temperatures and chemical corrosion. Some extreme scenarios even use ceramic materials (such as alumina ceramics) to ensure the sensor works normally in the temperature range of -40℃~125℃. For sensitive components, the detection electrodes of gas sensors need to use poison-resistant precious metal alloys (such as platinum-palladium alloys) to avoid failure when exposed to sulfur- and silicon-containing gases for a long time. The piezoelectric elements of impact sensors need to use PZT ceramics with a high electromechanical coupling coefficient, paired with impact-resistant packaging materials (such as epoxy resin potting) to prevent vibration from damaging the components. In addition, industrial and special sensors also need high protection levels, usually reaching IP67 or IP68, preventing dust and liquid from invading internal circuits through designs like sealing rings and waterproof breathable membranes.
II. Sensor Function Innovation and Structural Design Guided by Scenarios
Consumer Scenario Wearable Sensors: Lightweight and Low Power Consumption as Core Design Orientation
Consumer scenario wearable devices use smart bracelets, watches, and earphones as carriers. The core needs are to meet users' daily health monitoring, sports recording, and convenient interaction, while taking into account wearing comfort and battery life. Therefore, sensor design needs to achieve a balance among functional practicality, power consumption control, and volume miniaturization.
1. Functional Parameter Design: Matching the Demand Boundaries of Daily Scenarios
Based on typical user usage scenarios, the functional parameters of consumer-grade sensors need to accurately cover demands and avoid over-design:
(1) Heart rate monitoring sensor: Targeting resting heart rate tracking and moderate-to-high intensity sports monitoring scenarios, the design measurement range is 0-200bpm, covering the complete range of normal resting state (40-100bpm) and sports state (120-180bpm); accuracy is controlled at static ±2bpm and dynamic ±5bpm, which not only meets the reference value of health data but also avoids power loss caused by excessively high accuracy; the default sampling rate is 50Hz, which can be increased to 100Hz in sports mode, balancing data real-time performance and power consumption.
(2) Accelerometer: To achieve step counting and sports mode recognition (walking, running, cycling), the design range is ±8g (the acceleration of ordinary people's daily activities is mostly within ±2g, the peak of running and jumping is about ±6g, leaving a 2g margin to prevent overload); the resolution is not lower than 16 bits to ensure no missed or extra counts in step counting; the output data rate supports 10Hz-100Hz adjustable, with low rate reducing power consumption in static state and high rate ensuring data continuity in sports.
(3) Bone conduction sensor (smart earphones): Targeting clear calls during sports and avoiding ear canal blockage, the design vibration frequency range is 20Hz-20kHz (covering the human audible sound domain), the output sound pressure level is ≥100dB to ensure sound quality clarity, the distortion is ≤1% to reduce sound distortion, and it supports low-frequency vibration filtering parameters to suppress environmental interference such as wind noise and clothing friction.
2. Performance Requirement Design: Balancing User Experience and Device Battery Life
Users in consumer scenarios are highly sensitive to battery life. Sensors need to achieve synergy among low power consumption, stability, and anti-interference:
(1) Low power consumption requirements: The working current of the heart rate sensor is ≤1mA (reduced to below 0.5mA in static monitoring mode), and the standby current is ≤10μA; the static current of the accelerometer is ≤50μA, and the sports mode current is ≤200μA; the average current of the ambient light sensor is ≤10μA, ensuring that smart bracelets/watches have a battery life of 7-14 days, and smart earphones have a single battery life of 6-8 hours.
(2) Stability requirements: Within the daily ambient temperature range of -10℃-45℃, the accuracy drift of the heart rate sensor is ≤±1bpm, and the zero-bias stability of the accelerometer is ≤±5mg, avoiding data anomalies caused by temperature changes; the vibration amplitude deviation of the bone conduction sensor is ≤5%, ensuring stable sound quality during long-term wearing.
(3) Anti-interference requirements: The heart rate sensor resists the impact of skin sweating through waterproof coating design, and filters arm shaking interference with a three-axis accelerometer compensation algorithm; the accelerometer has a built-in high-frequency vibration filtering module to eliminate arm shaking noise during running; the bone conduction sensor uses a shock-proof buffer structure to reduce the transmission of external low-frequency noise (such as clothing friction during sports).
3. Structural Design: Adapting to Wearable Forms and Ergonomics
The sensor structure needs to be miniaturized and fit the human body, while cooperating with the overall form of the device to achieve hidden integration:
(1) Smart bracelet/watch sensor module: Adopts SMD (Surface Mount Device) packaging. The size of the heart rate sensor is controlled within 3×3×1mm, integrated with the accelerometer and ambient light sensor on the same PCB (Printed Circuit Board); it is laid out in the raised area on the back of the device close to the skin (raised height ≤2mm to avoid digging into the hand), surrounded by a black silicone light-blocking ring to prevent ambient light from interfering with photoelectric detection from the side; the PCB adopts a 4-layer board design, with sensor components arranged on the top layer, grounding on the bottom layer, and signal transmission in the middle layer to reduce electromagnetic interference.
(2) Smart earphone bone conduction sensor: The core piezoelectric ceramic vibration unit size is compressed to 10×8×1mm, packaged in a hard plastic shell that fits the curve of the mastoid bone behind the ear; the shell and the earphone body are connected by Shore 30A soft glue to improve wearing comfort; a 0.5mm thick nickel foam shock-proof buffer layer is set under the vibration unit to reduce noise generated by vibration transmission to the earphone body and protect the sensor from impact damage.
Medical Scenario Wearable Sensors: High Precision and Biocompatibility as Design Core
Medical scenario wearable devices need to meet clinical-grade monitoring needs. The core goal is to provide reliable data for disease diagnosis and treatment effect evaluation. Therefore, sensor design must strictly follow medical device standards, reaching clinical requirements in accuracy, stability, and biocompatibility, while taking into account the comfort of long-term wearing.
1. Functional Parameter Design: Meeting Clinical Monitoring Accuracy Requirements
The functional parameters of medical-grade sensors need to be benchmarked against clinical detection equipment to ensure data is medically usable:
(1) Continuous Glucose Monitoring (CGM) sensor: Targeting the dynamic blood glucose monitoring needs of diabetic patients, the design measurement range is 1.1-22.2mmol/L (covering the full range of hypoglycemia, normal blood glucose, and hyperglycemia), and the accuracy error needs to be controlled within ±10% (complying with the international ISO15197:2013 standard). The sampling interval is 1-5 minutes, which can reflect blood glucose fluctuation trends in real time while avoiding excessive power consumption caused by frequent sampling; it also supports the calculation of glucose concentration change rate, providing parameter basis for hypoglycemia/hyperglycemia warnings.
(2) Electrocardiogram (ECG) patch sensor: To achieve arrhythmia screening and myocardial ischemia monitoring, the design sampling rate is ≥500Hz (meeting the clinical electrocardiogram's requirements for capturing waveform details), resolution ≥16 bits, input impedance ≥10MΩ (reducing the interference of skin contact impedance on signals), common-mode rejection ratio ≥80dB (filtering power frequency interference and electromyography noise), capable of continuously recording 24-72 hours of ECG data, and supporting the extraction of clinical indicators such as heart rate variability (HRV) and ST-segment deviation.
(3) Smart blood pressure monitor sensor (wrist/arm type): Targeting the daily blood pressure monitoring of hypertensive patients, the design measurement range is 60-200mmHg (systolic) / 40-130mmHg (diastolic), and the accuracy needs to meet the international standard of ±3mmHg. The sampling rate is 100Hz-200Hz (ensuring the integrity of the pulse wave signal), and it supports dynamic adjustment parameters of cuff pressure, automatically adjusting the inflation pressure according to the user's arm circumference to avoid discomfort from overpressure or inaccurate measurement.
2. Performance Requirement Design: Ensuring Clinical Reliability and Long-Term Wearing Safety
The performance requirements for sensors in medical scenarios are much higher than those for consumer-grade. They need to reach medical device standards in stability, biocompatibility, and anti-interference capabilities:
(1) High stability requirements: Within the normal human body temperature range of 35℃-42℃, the blood glucose measurement error drift of the CGM sensor is ≤±5%, and the accuracy attenuation does not exceed 10% within 14 days of continuous operation; the ECG patch sensor has a heart rate measurement error of ≤±1 beat/min and an arrhythmia detection accuracy of ≥95% in static and light activity states; the smart blood pressure monitor sensor has a measurement error of ≤±5mmHg in different postures (sitting, standing), ensuring data is not affected by postural changes.
(2) Biocompatibility requirements: Direct contact with the skin must pass the ISO 10993 biocompatibility test. The subcutaneous probe of the CGM sensor uses medical-grade stainless steel or polyimide material, coated with a heparin coating to reduce the risk of tissue rejection and inflammation; the electrode pads of the ECG patch use silver/silver chloride gel material, which ensures conductivity while avoiding skin allergies or irritation caused by long-term wearing; the sensor packaging material needs to use medical-grade silicone or polyurethane, with breathable and waterproof characteristics to reduce skin stuffiness.
(3) Strong anti-interference requirements: The CGM sensor needs to resist the corrosion of sweat and tissue fluid, filter the micro-displacement interference of the probe caused by movement, and use dual-electrode differential detection technology to reduce environmental electromagnetic noise; the ECG patch has a built-in power frequency notch filter (50Hz/60Hz) and an electromyography filter (10Hz-300Hz) to eliminate mains interference and noise generated by muscle contraction; the smart blood pressure monitor uses the pulse wave oscillometric method combined with the Korotkoff sound method, filtering measurement errors caused by cuff looseness and user talking through algorithms.
3. Structural Design: Balancing Clinical Practicality and Wearing Comfort
The structural design of medical wearable sensors needs to balance data collection accuracy and long-term wearing experience, while considering the convenience of clinical operations:
(1) Continuous Glucose Monitoring (CGM) sensor: Adopts an integrated "probe + transmitter" design. The probe length is 5-8mm (adapting to subcutaneous tissue depth), and the diameter is ≤1mm (reducing implantation pain). A micro glucose oxidase biosensor is set at the end of the probe; the transmitter part size is controlled within 20×30×5mm, weight ≤10g, fixed on the back with medical-grade adhesive tape, and the edges of the tape are rounded (radius ≥3mm) to avoid scratching the skin; the transmitter connects to the mobile phone via low-power Bluetooth, has a built-in battery capacity of ≥200mAh, supports 14 days of continuous power supply, and has a waterproof rating of IPX7 (can be worn while bathing).
(2) Electrocardiogram (ECG) patch sensor: Adopts a flexible PCB board design, with an overall thickness of ≤2mm and weight ≤5g, fitting the chest curve; the electrode pad layout is 3-lead or 5-lead, with an electrode diameter of 15-20mm, covered with a conductive gel layer. The gel layer uses a sustained-release formula to ensure stable conductivity within 72 hours; the edges of the sensor use a gradient thickness design (transitioning from 2mm at the center to 1mm at the edges) to reduce detachment caused by clothing friction, and are equipped with detachable medical adhesive tapes for easy replacement without damaging the skin.
(3) Smart blood pressure monitor sensor (wrist type): Adopts an integrated "cuff + sensor module" design. The cuff material is a mixture of breathable mesh and elastic fibers, fitting different wrist circumferences (13-20cm); the sensor module has built-in pressure and pulse wave sensors. The pressure sensor uses a micro piezoresistive chip (size ≤5×5mm), installed on the inner side of the cuff close to the artery, and fixed through an arc-shaped bracket to ensure close contact with the skin during measurement.
Industrial Scenario Wearable Sensors: Explosion-proof, Impact-resistant, and Wide-temperature Operation as Design Core
Industrial scenario wearable devices are mainly used in fields such as petrochemicals, mining, intelligent manufacturing, and construction. The core goal is to monitor the vital signs, working posture, and environmental risks of operators in real time through sensors, achieving a trinity of intelligent management: "personnel safety warning, operation efficiency improvement, and equipment collaborative operation." Unlike consumer-grade and medical-grade scenarios, industrial scenarios have complex working conditions such as flammable and explosive environments, high temperature and humidity, strong electromagnetic interference, and frequent mechanical shocks. Therefore, sensor design must strictly follow industrial safety standards, reaching industrial-grade requirements in explosion-proof performance, impact resistance, wide-temperature operating range, and chemical corrosion resistance.
1. Functional Parameter Design: Adapting to Complex Industrial Working Environments
Industrial scenario sensors need to cover functions such as personnel safety monitoring and equipment operation assistance. Parameter design needs to meet high-intensity operation needs:
(1) Industrial safety helmet sensor: Targeting high-altitude operation and fall risk monitoring, it integrates a three-axis accelerometer and a tilt sensor. The accelerometer range needs to reach ±16g (covering the instantaneous impact acceleration during a fall), and the sampling rate is ≥500Hz (ensuring the capture of millisecond-level fall signals); the tilt sensor measurement range is 0-360°, accuracy ±1°, which can monitor the head tilt angle of operators in real time to determine if they are in a dangerous posture (such as excessive head up or side tilt imbalance). At the same time, it integrates environmental temperature and humidity sensors, with a temperature measurement range of -20~85℃ and humidity 0%-100%RH, and accuracies of ±1℃ and ±5%RH respectively, used for warning harsh environments such as high temperature and high humidity.
(2) Smart bracelet (industrial version): To monitor the vital signs and fatigue status of operators, the heart rate sensor measurement range is extended to 0-220bpm (covering the heart rate peak under high-intensity operations), accuracy ±2bpm, supporting heart rate variability (HRV) analysis, and judging personnel fatigue levels through HRV parameters (such as SDNN, RMSSD); the blood oxygen sensor measurement range is 70%-100%, accuracy ±2%, which can warn of low blood oxygen caused by hypoxic environments (such as underground mines, enclosed spaces). In addition, it integrates an NFC (Near Field Communication) module, supporting work card swiping and equipment start/stop authorization. The NFC communication distance is ≤5cm, and the recognition speed is ≤0.3 seconds, meeting the needs of fast operations in industrial sites.
(3) Foot monitoring shoe sensor: Targeting operators who stand and walk for a long time (such as production line workers, warehouse porters), it integrates a pressure sensor array. Each insole is distributed with 8-12 pressure sensing points. A single sensor range is 0-200kg, accuracy ±5kg, and sampling rate 50Hz. It can monitor foot pressure distribution in real time, judging whether the standing posture is correct and whether there is excessive unilateral load; at the same time, combined with the accelerometer to judge walking steps and gait abnormalities (such as limping), providing data support for preventing occupational lumbago and plantar fasciitis.
2. Performance Requirement Design: Meeting Industrial-grade Safety and Durability Standards
Industrial scenarios have stringent performance requirements for sensors, needing explosion-proof, impact-resistant, wear-resistant, and wide-temperature working capabilities:
(1) Explosion-proof performance requirements: Sensors applied in flammable and explosive environments such as petrochemicals and coal mines need to comply with ATEX explosion-proof certification (such as II2G Ex d IIB T4 Gb), adopt intrinsically safe design, working current ≤30mA, working voltage ≤12V, to avoid generating electric sparks; the shell adopts a flameproof structure and 316L stainless steel material, with a thickness of ≥2mm, capable of withstanding internal explosion pressure and preventing flame propagation to the external environment.
(2) Impact resistance and durability requirements: Industrial safety helmet sensors need to pass the IEC61010-1 impact test, capable of withstanding the impact of a 1kg steel ball falling from a height of 1m without damage; the smart bracelet shell uses polycarbonate (PC) material, with an anti-scratch coating on the surface (hardness ≥3H), capable of resisting daily collisions and friction; the pressure sensor of the foot monitoring shoe uses wear-resistant rubber packaging, with a Shore hardness of ≥60A, capable of withstanding ≥500,000 stepping cycles without failure.
(3) Wide-temperature and environmental adaptability requirements: Sensors need to work normally in the temperature range of -40℃-85℃, with a humidity adaptation range of 0%-95%RH (non-condensing); they must have an IP67 and above protection level. Industrial safety helmet sensors need to reach IP68 (can be soaked in 1m deep water for a long time) to prevent rain, dust, and oil from invading; at the same time, they can resist industrial electromagnetic interference (such as electromagnetic radiation generated by frequency converters and welding machines), with a common-mode rejection ratio of ≥80dB, ensuring stable data transmission.
3. Structural Design: Balancing Safety Protection and Operation Convenience
The structural design of industrial wearable sensors needs to be integrated with protective equipment to avoid affecting operations and facilitate maintenance and replacement:
(1) Industrial safety helmet sensor: Integrates accelerometer, tilt, and temperature/humidity sensors into a small module (size ≤40×30×15mm), installed in a dedicated slot on the inner side, fixed by clips for easy disassembly and replacement; gaps are filled with 5mm thick EVA foam to protect the sensor from damage upon impact; the sensor module is connected to the transmitter at the back of the safety helmet through wires. The transmitter has a built-in antenna, supporting LoRaWAN or 4G communication. The transmitter shell has a waterproof interface for charging and data export.
(2) Industrial smart bracelet: The shell is made of PC+ABS alloy material, and the strap is made of fluoroelastomer material (oil-resistant, chemical corrosion-resistant). The strap buckle is made of stainless steel, capable of withstanding ≥1000 opening and closing cycles without damage; the screen uses a semi-transflective LCD screen, with visibility ≥300cd/m² under strong light to avoid sunlight affecting data reading; the sensor module is located inside the bracelet body, laid out in layers with the battery and motherboard. The sensor area is sealed to prevent sweat and rain from seeping in. The battery uses a replaceable design, with a battery life of ≥7 days. It only requires unscrewing the back cover for replacement, without tools.
(3) Foot monitoring shoe sensor: The pressure sensor array is integrated inside a custom insole. The insole material is breathable mesh + polyurethane foam, with a thickness of ≤10mm; the sensor lines use flexible wires (diameter ≤0.5mm), embedded in the insole interlayer to avoid damage from stepping; a small transmitter (size ≤30×20×10mm) is set at the heel of the insole, connecting to a mobile phone or industrial terminal via Bluetooth 5.0. The transmitter uses a magnetic charging design, with the charging interface hidden at the edge of the insole, waterproof rating IP67, charging time ≤2 hours, and battery life ≥12 hours.
Special Scenario Wearable Sensors: Extreme Environment Tolerance and Rapid Danger Response as Design Core
Special scenario wearable devices are mostly used in extreme environments such as military operations, fire rescue, deep-sea diving, and polar scientific expeditions. The core need is to monitor personnel vital signs and environmental hazard factors in real time under harsh conditions such as high temperature, high pressure, strong impact, and strong radiation, and possess functions such as rapid warning and emergency communication. Therefore, sensor design needs to break through conventional performance limits, meeting the requirements of tolerance, reliability, and response speed in extreme environments, while taking into account the lightweight of the device and the non-interference with personnel movements, ensuring safety guarantees and decision-making basis for users at critical moments.
1. Functional Parameter Design: Meeting Monitoring and Warning Needs in Extreme Environments
(1) Bulletproof vest integrated sensor (explosion-proof security scenario): Targeting the monitoring needs of ballistic impact and explosion shock waves, it integrates piezoelectric films and accelerometers. The piezoelectric film needs to have ultra-high sensitivity, capable of capturing shock wave pressure changes above 0.1MPa, with a response time of ≤1ms, triggering warning signals at the moment of explosion; the accelerometer range needs to reach ±50g, sampling rate ≥1000Hz, capable of accurately judging the location and intensity of bullet or shrapnel impact. Combined with a heart rate sensor (measurement range 0-220bpm, accuracy ±2bpm) and a body temperature sensor (measurement range 35℃-42℃, accuracy ±0.5℃), it monitors in real time whether the wearer is injured or showing symptoms of shock. In addition, it integrates a GPS positioning module, with positioning accuracy ≤5m, supporting Beidou/GLONASS dual-mode, ensuring accurate positioning in complex terrains.
(2) Firefighting suit integrated sensor (fire rescue scenario): To cope with high temperature and toxic gas environments, it integrates temperature sensors, gas sensors, and heart rate sensors. The temperature sensor adopts a thermocouple design, with a measurement range of -20℃-1000℃ and accuracy of ±2℃. It can monitor the outer layer temperature of the firefighting suit in real time, automatically alarming when the temperature exceeds 300℃ (the high-temperature resistance limit warning value of the firefighting suit); the gas sensor needs to detect CO, H₂S, and O₂ simultaneously. CO measurement range is 0-1000ppm (accuracy ±5%FS), H₂S measurement range is 0-100ppm (accuracy ±3%FS), O₂ measurement range is 0-25%VOL (accuracy ±0.5%VOL). It immediately issues audible and visual alarms when toxic gas concentration exceeds the standard or oxygen content is below 19.5%; the heart rate sensor needs to have anti-high-temperature interference capabilities, maintaining a measurement accuracy of ±3bpm in a 50℃ environment to judge whether firefighters are physically exhausted due to high temperature and hypoxia.
(3) Deep-sea diving suit sensor (deep-sea exploration scenario): Targeting high pressure, low temperature, and dark environments, it integrates pressure sensors, temperature sensors, and attitude sensors. The pressure sensor measurement range is 0-100MPa (corresponding to a deep-sea depth of 10,000 meters), accuracy ±0.5MPa, which can monitor the pressure difference inside and outside the diving suit in real time to avoid diving suit rupture caused by pressure imbalance; the temperature sensor measurement range is -2℃-30℃ (common deep-sea temperature range), accuracy ±0.2℃, cooperating with the heating system to adjust the temperature inside the diving suit; the attitude sensor adopts a nine-axis sensor (three-axis accelerometer + three-axis gyroscope + three-axis magnetometer), measurement range ±16g (acceleration), ±2000°/s (angular velocity), accuracies of ±0.01g and ±0.1°/s respectively, which can accurately judge the diver's attitude (such as whether tilting or flipping) to avoid getting lost in the dark environment. At the same time, it integrates an underwater acoustic communication module, supporting short-distance data transmission within 1000 meters, sending sensor data to the surface command center in real time.
2. Performance Requirement Design: Breaking Through Performance Limits in Extreme Environments
The performance requirements for sensors in special scenarios far exceed those in conventional scenarios, needing to reach stringent standards in tolerance, reliability, and response speed:
(1) Extreme environment tolerance requirements: Bulletproof vest sensors need to pass military standard tests, capable of withstanding a temperature range of -40℃-70℃, and working continuously for 72 hours without failure in a 95% RH (30℃) environment; firefighting suit sensors need to have high-temperature aging resistance, with accuracy attenuation not exceeding 10% after continuous operation for 30 minutes in a 200℃ environment; deep-sea diving suit sensors need to pass a 100MPa high-pressure test (equivalent to 10,000 meters deep-sea pressure), with no shell deformation and no circuit short circuit, and a startup time of ≤1 second at -2℃ low temperature to avoid delayed sensor response caused by low temperature.
(2) High reliability and anti-interference requirements: Military scenarios require anti-electromagnetic pulse interference capabilities, with a data transmission bit error rate of ≤0.1% in a 100V/m electromagnetic radiation environment; firefighting suit gas sensors need to have anti-dust interference capabilities, using a dust-proof filter + self-cleaning algorithm, maintaining measurement accuracy in an environment with dust concentration ≥10mg/m³; deep-sea sensors need to resist seawater corrosion, with shells made of titanium alloy material, coated with polytetrafluoroethylene. Salt spray testing (5% NaCl solution, 35℃) for 3000 hours shows no corrosion traces. Circuit interfaces use waterproof aviation plugs, reaching protection level IP68.
(3) Rapid response and low power consumption requirements: The danger response time of bulletproof vest sensors is ≤200ms (from detecting impact/explosion to issuing warning signals), ensuring that wearers or rear command centers have enough time to take emergency measures; the audible and visual alarm decibel of the firefighting suit alarm system is ≥110dB (at a distance of 1 meter), with a flash frequency of 10-15 times/second, ensuring rapid perception in noisy fire scenes; deep-sea sensors have built-in high-energy lithium batteries, with a battery life of ≥48 hours (in deep-sea low-temperature environments), supporting low-power mode, with a current of ≤10μA in non-working states to avoid frequent battery replacement affecting operations.
3. Structural Design: Balancing Protection Performance and Wearing Flexibility
Special scenario wearable sensors need to be designed in integration with professional protective equipment, neither affecting the original protective functions of the equipment nor compromising the monitoring effect of the sensors:
(1) Bulletproof vest integrated sensor: Adopts a flexible patch design. The piezoelectric film sensor is cut into a shape matching the bulletproof insert plate (such as 20×30cm), attached to the inner side of the insert plate, and covered with a layer of bulletproof nylon cloth to avoid direct damage to the sensor by shrapnel; the accelerometer and heart rate sensor are integrated into a small module (size ≤30×20×5mm), installed on the inner side of the bulletproof vest close to the heart. The module is fixed by magnets for easy disassembly and maintenance; all sensor lines use tensile-resistant wires (breaking strength ≥50N), embedded in the interlayer of the bulletproof vest to avoid wire breakage during movement. Data is transmitted to the tactical terminal via a wireless transmission module (supporting military encryption protocols), with a transmission distance of ≥500 meters (unobstructed environment).
(2) Firefighting suit integrated sensor: Temperature sensors are distributed, with 6-8 temperature measurement points set on the torso and limbs of the firefighting suit. The probes are made of high-temperature resistant ceramic material, with an exposed diameter of ≤3mm to avoid snagging on obstacles; the gas sensor module is installed at the collar of the firefighting suit, with the air inlet facing outward, equipped with a detachable dust-proof filter (filter pore size ≤0.5mm) for easy cleaning and replacement; sensor lines are wrapped in high-temperature resistant silicone (temperature resistance level -60℃-260℃), arranged along the stitching of the firefighting suit, not conflicting with the reflective strips and waterproof coating of the firefighting suit. The overall weight increase is ≤200g, not affecting the action flexibility of firefighters.
(3) Deep-sea diving suit sensor: The pressure sensor is installed on the inner side of the transparent observation window at the wrist of the diving suit, packaged with sapphire glass, which can withstand high pressure and allow divers to view pressure data; the attitude sensor is integrated inside the diving helmet, close to the center of gravity of the head, reducing the impact of body posture changes on measurement accuracy; all sensors are connected to the main control module on the back of the diving suit through waterproof wires (size ≤150×100×50mm, weight ≤500g). The main control module has a pressure-resistant shell (titanium alloy, wall thickness ≥8mm), built-in underwater acoustic communicator and GPS module, which can synchronously transmit data to surface ships, and supports emergency signal sending functions (triggered by long press for 3 seconds) to send positioning signals when the diver is out of contact.
III. Multi-Sensor Fusion and System Integration Technology
Multi-Sensor Parameter Fusion Algorithms
1. Physiological parameter fusion: Targeting the precise monitoring needs of wearable devices for human physiological states, a collaborative working mode of heart rate, blood oxygen, body temperature, etc., is adopted. Through optimizing the Kalman filtering algorithm, multi-source physiological data is dynamically fused. Specifically, using the prediction-update mechanism of Kalman filtering, measurement errors caused by motion interference and environmental light changes in a single sensor are eliminated. For example, in sports scenarios, the heart rate sensor is easily affected by arm shaking. Combined with the pulse wave signal of the blood oxygen sensor for correction, the heart rate measurement accuracy error can be controlled within ±2bpm, while improving the stability of blood oxygen saturation measurement, ensuring continuous and reliable physiological parameter output.
2. Motion parameter fusion: To achieve accurate recognition of human posture and motion states, data from accelerometers, gyroscopes, and geomagnetic sensors are integrated, using the Mahony algorithm (or complementary filtering algorithm) for attitude calculation. Linear acceleration is obtained through the accelerometer, angular velocity data is provided by the gyroscope, and the direction reference is determined by the geomagnetic sensor. The Mahony algorithm calculates the pitch, roll, and heading angles of the device wearer in real time through weighted fusion of the three data, solving the problems of drift in static states and insufficient accuracy in dynamic states of a single sensor, making the posture recognition error ≤±1°, supporting automatic recognition of various sports modes such as running, cycling, and swimming, as well as rapid judgment of dangerous postures such as falls and imbalance.
3. Environmental parameter fusion: Facing the environmental risk monitoring needs in industrial and special scenarios, data from temperature, humidity, and gas sensors (such as CO, H₂S, O₂) are fused, and an environmental risk assessment model is constructed based on the fuzzy logic fusion algorithm. The fuzzy logic algorithm can effectively handle uncertain and non-linear data output by sensors. For example, in an industrial workshop, when the temperature >35℃, humidity >80%RH, and CO concentration >24ppm, the algorithm will comprehensively judge the environment to be in a "moderate risk" state based on preset membership functions and rule bases. Compared with single-sensor alarms, it can avoid false alarms caused by environmental parameter fluctuations, improving the accuracy of environmental risk warnings, and reducing the false alarm rate to below 5%.
Solving Key Problems in System Integration
1. Power consumption optimization technology: Targeting the pain point of short battery life in wearable devices, an "edge computing + dynamic power management" architecture is adopted in the system integration stage. On the one hand, the preprocessing of multi-sensor data (such as noise reduction, feature extraction) is deployed on the edge computing unit at the device end, reducing the energy consumption caused by raw data transmission; on the other hand, through a dynamic wake-up mechanism, the sensor working mode is intelligently adjusted according to the user's usage scenario. For example, during nighttime sleep monitoring, the sampling rate of the heart rate sensor is reduced to 1Hz, and unnecessary environmental sensors are turned off, reducing the overall power consumption of the device by 30%-40%, extending the battery life to 7-14 days, meeting daily usage needs.
2. Miniaturized integration design: To ensure the wearing comfort of wearable devices, chip-level integration and flexible circuit design technologies are adopted. At the hardware level, multiple sensors (such as heart rate, accelerometer, temperature sensors) and a microcontroller (MCU, Microcontroller Unit) and wireless communication modules (Bluetooth, LoRa) are integrated into a single System-in-Package (SiP) chip, reducing the hardware volume by more than 30%; at the circuit design level, flexible PCB (Printed Circuit Board) boards are used, paired with ultra-thin batteries (thickness ≤2mm) and lightweight shells (weight ≤10g), controlling the device thickness within 5mm, which can be seamlessly integrated into small wearable carriers such as bracelets, watches, and patches without affecting users' daily activities.
3. Multi-system compatibility guarantee: To achieve collaborative work between wearable devices, mobile phones, industrial terminals, and cloud platforms, standardized communication protocols and data interfaces are adopted during system integration. For example, sensor data is transmitted via Bluetooth 5.0 (or LoRaWAN) protocol, following the IEEE11073 medical device communication standard, ensuring that physiological data can be directly connected to medical management platforms; at the same time, it supports OTA (Over-The-Air) upgrade functions, which can remotely update sensor fusion algorithms and system firmware, solving the data interoperability problem between different devices and platforms, improving the scalability and applicability of wearable systems, and meeting the usage needs of multiple scenarios such as consumer, medical, and industrial.
Typical Application Case Analysis
1. Smart sports watch: Taking a certain brand's professional sports watch as an example, it integrates 6 types of sensors: heart rate, blood oxygen, accelerometer, gyroscope, geomagnetic, and barometric pressure. It fuses physiological parameters (heart rate, blood oxygen) through the Kalman filtering algorithm, and motion parameters (accelerometer, gyroscope, geomagnetic) through the Mahony algorithm, achieving multi-dimensional sports monitoring. In the running scenario, the fused heart rate data error is ≤±1bpm, the measurement accuracy of step frequency and stride length is improved by 20%, and sports intensity curves can be generated in real time; in the mountaineering scenario, the fusion of the barometric pressure sensor and accelerometer can accurately calculate altitude changes (error ≤±5m). Combined with environmental temperature sensor data, it warns of high-altitude hypoxia risks, providing scientific guidance for sports enthusiasts.
2. Industrial inspection safety helmet: In scenarios such as petrochemicals and mines, the industrial inspection safety helmet integrates gas (CO, H₂S, O₂), temperature, humidity, three-axis accelerometer, and tilt sensors, fusing environmental parameters and posture parameters through the fuzzy logic algorithm. When inspectors enter a toxic gas leak area, the fusion of gas sensor data with temperature and humidity data can trigger an audible and visual alarm (≥110dB) within 1 second; when a person falls (acceleration >10g, tilt angle >45°), the fusion of accelerometer and tilt sensor data can automatically send positioning information (positioning accuracy ≤5m) and distress signals to the backend command center, shortening the time from danger occurrence to warning response to within 3 seconds, significantly improving the safety of industrial inspections.
3. Health monitoring bracelet (postoperative rehabilitation scenario): Targeting the rehabilitation monitoring needs of postoperative patients, the health bracelet integrates electrocardiogram (ECG), electromyography (EMG), and accelerometer sensors. By fusing ECG data and EMG data, it achieves precise evaluation of muscle activity status. For example, in hand postoperative rehabilitation, the EMG sensor captures muscle electrical signals, and the accelerometer records hand movement trajectories. The data of the two are fused through a complementary filtering algorithm to judge the patient's hand activity range and muscle exertion. Combined with the heart rate changes monitored by the ECG sensor, it evaluates whether the rehabilitation training intensity is appropriate. Doctors can view the fused rehabilitation data through the cloud platform, formulate personalized training plans, and shorten the patient's rehabilitation cycle by 15%-20%.
IV. Innovative Application Cases and Development Trends of Wearable Sensors
Selected Innovative Application Cases
1. Flexible wearable electronic skin: High-sensitivity stress-temperature dual-parameter monitoring technology based on graphene heterojunctions
(1) Technical breakthroughs: Breaking through the bottlenecks of single-parameter monitoring and signal distortion under high stretching in traditional electronic skins, a "graphene/polyimide heterojunction" structure is adopted to simultaneously achieve high-precision synchronous monitoring of pressure, tensile strain, and temperature, solving the problem that physiological signals are easily interfered with during movement.
(2) Sensitive mechanism and material innovation:
Stress sensing mechanism: Single-layer graphene is grown on a polyimide (PI) substrate by chemical vapor deposition (CVD) to construct a "graphene-PI" heterojunction interface. When subjected to external stretching or pressing, the Schottky barrier height of the heterojunction interface changes, leading to a change in device resistance (sensitivity factor GF=50, much higher than the GF=2 of traditional metal strain gauges).
Temperature sensing mechanism: Utilizing the characteristic that the carrier concentration of graphene changes with temperature, micro platinum electrodes are integrated in the heterojunction region. By measuring the volt-ampere characteristic curve between the electrodes, temperature quantification is realized (temperature coefficient α=0.015/℃).
Material optimization: To improve stretching stability, 10% elastomer (TPU) is doped in the PI substrate, increasing the elongation at break of the substrate from 50% to 300%; at the same time, a "wrinkle structure" design is adopted, allowing the graphene layer to unfold through wrinkles rather than break during stretching, ensuring signal linearity at a 500% stretching rate.
(3) Core performance parameters and test data:
(4) Typical applications and value: In the field of rehabilitation medicine, it is used for fine motor rehabilitation training of fingers in stroke patients. After wearing, the electronic skin can synchronously monitor finger bending angle (accuracy ±0.5°), pressing force (resolution 0.1N), and skin temperature (reflecting local blood circulation). Data is transmitted to the rehabilitation evaluation system via Bluetooth. Compared with traditional evaluation methods (doctor's naked-eye observation + scale scoring), this electronic skin improves the accuracy of motor function evaluation from 75% to 92%, shortens the training plan adjustment cycle from once a week to once a day, and reduces the recovery time of patients' finger grip strength by an average of 28 days.
2. Implantable blood glucose monitoring sensor: Long-term calibration-free technology based on nano-gold-enzyme synergistic immobilization
(1) Technical breakthroughs: Solving the pain points of "fast enzyme activity attenuation" and "frequent calibration required" in traditional implantable sensors, adopting "nano-gold particle anchoring + multi-layer film packaging" technology, stably fixing glucose oxidase (GOD) on the electrode surface, extending the sensor life from 7 days to 14 days, and reducing the calibration frequency from twice a day to once every 3 days.
(2) Sensitive mechanism and material innovation:
Enzyme immobilization technology innovation: Nano-gold particles (diameter 20nm) are electrodeposited on the surface of the platinum working electrode. Utilizing the high specific surface area and biological affinity of nano-gold, GOD molecules are anchored on the particle surface; then, through layer-by-layer self-assembly technology, 3 layers of polyelectrolyte membranes (PAH/PSS) are wrapped to form a "nano-gold-GOD-polyelectrolyte" composite structure. This structure can prevent GOD loss while allowing glucose molecules to penetrate quickly (diffusion coefficient D=1.2×10⁻⁵cm²/s).
Anti-interference design: A polytetrafluoroethylene (PTFE) hydrophobic layer is integrated around the reference electrode to inhibit the diffusion of interfering substances such as ascorbic acid and uric acid, reducing the proportion of interference signals from the traditional 15% to below 3%.
(3) Core performance parameters and test data:
(4) Typical applications and value: In the management of type 2 diabetic patients, after the sensor is implanted subcutaneously in the abdomen, it collects glucose data once every 5 minutes and transmits it to a mobile phone APP via NFC. When blood glucose is below 3.9mmol/L (hypoglycemia) or above 16.7mmol/L (hyperglycemia), the APP automatically issues an audible and visual alarm. A clinical study in a tertiary hospital showed that for patients using this sensor, the incidence of hypoglycemic events dropped from 4.2 times per month to 1.1 times, glycated hemoglobin (HbA1c) decreased by an average of 0.8%, the accuracy of insulin dosage adjustment increased by 35%, and the risk of complications caused by blood glucose fluctuations was reduced.
3. Industrial wearable smart protective gloves: Active injury prevention system based on multi-modal sensing fusion
(1) Technical breakthroughs: Integrating four types of sensors: pressure, capacitance, inertia, and temperature, combined with an edge computing chip, it realizes the trinity function of "danger prediction - active protection - emergency alarm," shifting hand injury prevention from "post-processing" to "pre-intervention."
(2) Sensing system design and innovation:
Multi-modal sensor layout: ① Capacitive proximity sensors (detection distance 0-10cm, resolution 0.1cm) are built into the fingertips to detect the distance from metal sharp edges and rotating parts; ② 3 carbon nanotube pressure sensors (range 0-200N, accuracy ±1N) are distributed on the palm to monitor grip force; ③ A 6-axis IMU (Inertial Measurement Unit) sensor (sampling rate 100Hz) is built into the wrist to identify abnormal hand movements (rapid impact actions); ④ Flexible temperature sensors (range -20-100℃, accuracy ±0.5℃) are embedded at the finger seams to detect contact with high-temperature objects.
Edge computing algorithm innovation: A lightweight convolutional neural network (CNN) is used to fuse multi-sensor data in real time, achieving millisecond-level danger judgment on the STM32L4 chip built into the glove (model inference time <20ms). For example, when the proximity sensor detects a distance of <3cm from a rotating part, and the IMU detects hand acceleration >5m/s², the system judges it as an "impact risk" and triggers the protection mechanism.
(3) Core performance and protection effect:
(4) Typical applications and value: In an automotive parts stamping workshop, when a worker wears this glove to operate a stamping machine, if the hand is mistakenly extended into the stamping area (proximity sensor detection distance <2cm), the glove will trigger airbag inflation 500ms before the stamping machine closes and send a stop signal to the machine tool control system.
Core Development Trends
Cross-disciplinary fusion trend of sensitive mechanisms: Future wearable sensors will draw more on principles from biomedicine, materials science, quantum technology, and other fields to develop new sensitive mechanisms. For example, mimicking human skin perception, developing "artificial tactile receptors" based on ion gels to achieve refined recognition of texture and hardness (resolution up to 1μm); utilizing the fluorescence characteristics of quantum dots to develop optical sensors that can detect multiple biomarkers (such as tumor markers, inflammatory factors), reducing the detection limit to the pg/mL level.
1. Micro-nano integration trend in manufacturing processes: Adopting a process combining MEMS (Micro-Electro-Mechanical Systems) and flexible electronics to achieve monolithic integration of sensors, signal processing circuits, and wireless transmission modules. For example, through wafer-level packaging technology, a 6-axis IMU, heart rate sensor, and Bluetooth chip are integrated on a 0.5mm thick flexible substrate. The device volume is reduced to 1/10 of the traditional discrete design, and power consumption is reduced by more than 40%. It is expected that by 2028, the penetration rate of micro-nano integrated wearable sensors in the consumer electronics field will exceed 70%.
2. Autonomous trend in energy supply: Breaking away from the dependence on lithium batteries, developing self-powered technology based on human body energy harvesting. For example, using lactic acid in human sweat to generate power through microbial fuel cells (power density up to 50μW/cm²) to power smart bracelet sensors; converting mechanical energy from walking into electrical energy through piezoelectric fibers (conversion efficiency up to 25%) to continuously power smart insole sensors. This autonomous energy supply will enable wearable devices to achieve "lifetime charging-free," solving the battery life anxiety problem.
3. Endogenous protection trend in data security: Targeting the data privacy issues of medical-grade wearable devices, developing "device-side encryption + federated learning" technology. Physiological data collected by sensors is directly encrypted at the device end (using the AES-256 algorithm), and raw data is not leaked during transmission; during model training, federated learning is adopted, and data analysis of multiple devices is completed locally, sharing only model parameters to avoid user privacy leakage. For example, a certain smart watch manufacturer has adopted this technology, reducing the leakage risk of heart rate, sleep, and other data to below 0.01%.
V. Market Application Prospects and Quantitative Analysis of Wearable Sensors
Global and Chinese Market Size and Growth Drivers
1. Overall market size:
According to data from Markets and Markets and the China Electronic Components Industry Association, the global wearable sensor market size reached 12.87 billion USD in 2024, a year-on-year growth of 19.2%; the Chinese market size was 3.52 billion USD (about 25.2 billion RMB), accounting for 27.3% of the global market, with a year-on-year growth rate of 23.5%, higher than the global average. It is expected that the global market will grow at a CAGR of 18.5%, and the scale is expected to exceed 30 billion USD by 2030; the CAGR of the Chinese market will reach 22.1%, and the scale will exceed 10 billion USD (about 71.5 billion RMB) by 2030, becoming the world's largest single market for wearable sensors.
2. Segment scale and proportion:
Divided by application fields, the global wearable sensor market in 2025 has shown a pattern of "consumer-grade dominance, with medical-grade and industrial-grade rising rapidly":
(1) Consumer-grade wearable sensors: The scale is about 7.63 billion USD, accounting for 59.3%, mainly applied in devices such as smart watches (heart rate, blood oxygen, accelerometer sensors), smart bracelets (pressure, temperature sensors), and TWS (True Wireless Stereo) earphones (bone conduction, touch sensors). Among them, in 2025, the shipment volume of heart rate sensors reached 820 million units, and blood oxygen sensors reached 570 million units, with year-on-year growth of 15.1% and 28.3% respectively (benefiting from the increase in users' health monitoring needs in the post-pandemic era).
(2) Medical-grade wearable sensors: The scale is about 3.26 billion USD, accounting for 25.3%, with the fastest growth rate (28.7% year-on-year). The core drivers are chronic disease management (such as diabetes, hypertension) and home elderly care needs. For example, the global shipment volume of Continuous Glucose Monitoring (CGM) sensors grew from 12 million units in 2021 to 40 million units in 2025, with a CAGR of 42.3%; the adoption rate of electrocardiogram (ECG) sensors in smart watches increased from 18% in 2021 to 35% in2025, driving the shipment volume to grow to 210 million units.
(3) Industrial and special wearable sensors: The scale is about 1.98 billion USD, accounting for 15.4%, with a year-on-year growth of 16.8%, mainly applied in scenarios such as intelligent manufacturing (smart gloves, safety helmet sensors), logistics and warehousing (wristband motion capture sensors), and public safety (bulletproof vest impact sensors). In 2025, the shipment volume of industrial smart glove sensors reached 2.1 million sets, a year-on-year growth of 33.8%; the shipment volume of smart safety helmet sensors was 1.8 million sets, a year-on-year growth of 27.5%, mainly benefiting from the demand for factory safety production transformation driven by the "Industrial Internet" policy.
3. Breakdown of growth drivers:
(1) Policy-driven: At the global level, in 2025, the US FDA accelerated the review and approval of 12 non-invasive blood glucose sensors for medical wearable devices; the EU's General Data Protection Regulation (GDPR) optimized the compliance of health data, promoting the commercialization of medical-grade products. At the domestic level, the "14th Five-Year Plan" for intelligent manufacturing development proposed that "the popularization rate of digital R&D and design tools in industrial enterprises above designated size will reach 90% by 2025," directly driving the demand for industrial wearable sensors; the "Healthy China 2030" Planning Outline encouraged the development of home medical devices. In 2024, the domestic medical wearable device subsidy policy covered 23 provinces, driving a 31% increase in terminal product sales.
(2) Demand-driven: The intensification of population aging promotes the demand for health monitoring sensors in home elderly care scenarios; under consumption upgrading, users' functional requirements for smart wearable devices have shifted from "basic step counting" to "medical-grade monitoring," driving the penetration rate of high-value sensors (such as ECG, PPG sensors); in the industrial field, the rise in labor costs makes enterprises tend to improve production efficiency through smart wearable devices (such as reducing work injury downtime, optimizing operation processes), driving the growth of industrial sensor procurement volume.
Market Competition Pattern: Differentiated Layout of Global Giants and Domestic Enterprises
1. Global Market Competition Pattern (by 2024 market share):
(1) International leading enterprises (total share about 62%):
Bosch: Share 18.3%, advantage areas are consumer-grade accelerometers and gyroscopes (shipment volume ranks first globally, accounting for 42% of the smart watch IMU sensor market). The 6-axis IMU sensor launched in 2024 (volume reduced by 30%, power consumption reduced by 25%) further consolidated its leading position.
STMicroelectronics: Share 15.1%, core products are pressure sensors and temperature sensors, accounting for 35% in the TWS earphone touch sensor market. It is also deploying medical-grade sensors (such as enzyme electrode sensors for CGM). In 2024, the proportion of medical business revenue increased to 22%.
Texas Instruments (TI): Share 12.7%, focusing on analog sensors (such as signal conditioning chips for heart rate sensors), deeply cooperating with terminal manufacturers such as Apple and Samsung. Its heart rate sensor chips have an adoption rate of over 60% in high-end smart watches.
Analog Devices, Inc. (ADI): Share 15.9%, advantage area is medical-grade sensors (such as ECG sensor modules). In 2024, it launched a single-lead ECG sensor integrating AI (Artificial Intelligence) algorithms, increasing the detection accuracy from 85% to 92%, with a market share of 30% among domestic medical wearable device manufacturers.
(2) Domestic enterprises (total share about 28%, an increase of 8 percentage points compared to 2021):
GoerTek: Share 7.2%, extending from consumer electronics OEM to sensor manufacturing. In 2024, the shipment volume of smart watch heart rate sensors reached 120 million units, accounting for 14.6% of the global market.
MEMSensing: Share 5.1%, focusing on MEMS sensors (accelerometers, gyroscopes). The adoption rate of its IMU sensors in Xiaomi and OPPO smart watches increased from 10% in 2021 to 28% in 2024, with a year-on-year shipment volume growth of 55%.
AAC Technologies: Share 6.8%, core products are acoustic sensors (bone conduction sensors) and pressure sensors, accounting for 22% in the TWS earphone sensor market. The ultra-thin pressure sensor (thickness 0.3mm) launched in 2024 has been applied to the touch keys of smart bracelets, with a shipment volume of 80 million units.
Nuoa Medical: Share 8.9%, focusing on the enzyme electrode technology of CGM sensors. In 2024, its domestic market share reached 25% (second only to Abbott). Its independently developed nano-gold enzyme immobilization technology extended the sensor life from 7 days to 14 days and reduced costs by 30%. It has entered the clinical supply chain of multiple tertiary hospitals.
2. Industry Chain Pattern:
(1) Upstream materials and components: Among global high-end materials, flexible substrate PI films are mainly monopolized by DuPont (US), Toray (Japan), and Ube Industries (Japan); there are no absolutely monopolistic enterprises in the fields of graphene and nano-gold particles, with core suppliers distributed in the US, Japan, South Korea, and mainland China. Domestic enterprises are gradually breaking through in the fields of graphene films and flexible PI films, with a significant increase in the usage rate in consumer-grade electronic skins, but the localization rate of high-end medical-grade materials is still less than 10%.
(2) Midstream sensor manufacturing: International manufacturers mainly adopt the IDM (Integrated Device Manufacturing) model (design + manufacturing + packaging), while domestic enterprises mostly adopt the Fabless model (design + outsourced manufacturing), relying on the MEMS production lines of foundries such as SMIC (Semiconductor Manufacturing International Corporation) and Hua Hong Semiconductor.
(3) Downstream terminal applications: The consumer-grade field is dominated by brands such as Apple, Samsung, Huawei, and Xiaomi (accounting for 72% of the global smart wearable device market combined). Sensor procurement tends to adopt an "international leader + domestic supporting" model (for example, Huawei smart watches use Bosch for main sensors and MEMSensing for auxiliary sensors); the medical-grade field is dominated by enterprises such as Abbott, Dexcom, and Nuoa Medical, with sensors and terminal devices deeply bound (for example, Nuoa Medical's CGM sensors are only supplied to its own brand and Mindray); the industrial-grade field is mainly B-end customers (such as automobile factories, logistics companies), and sensor manufacturers need to provide "hardware + algorithm + system integration" overall solutions (for example, the smart gloves provided by GoerTek for SAIC Motor include sensors, edge computing modules, and production management software).
Market Growth Points and Quantitative Predictions in the Next 5 Years
1. Segment Growth Predictions (2025-2030):
(1) Medical-grade wearable sensors: The CAGR is expected to reach 29.3%, and the scale will exceed 12 billion USD by 2030. Core growth points include: ① Non-invasive blood glucose monitoring sensors: As the technology matures (MARD value drops below 8%), the global penetration rate will increase from 5% in 2025 to 18% in 2030, with a shipment volume of 150 million units; ② Sleep apnea monitoring sensors: Smart pillows/bracelets integrating pressure, blood oxygen, and snoring sensors will benefit from the growth of the sleep disorder population (globally expected to increase from 1 billion in 2025 to 1.2 billion in 2030), with a shipment volume CAGR of 35%; ③ Rehabilitation medical sensors: Such as the application of flexible electronic skin in stroke rehabilitation. The global market scale will increase from 210 million USD in 2025 to 850 million USD in 2030, with a CAGR of 32%.
(2) Industrial and special wearable sensors: The CAGR is expected to reach 24.5%, and the scale will exceed 6 billion USD by 2030. Main driving factors: ① Driven by the "Intelligent Manufacturing 2025" plan, the popularization rate of smart wearable devices in domestic industrial enterprises will increase from 12% in 2025 to 35% in 2030, driving the shipment volume of industrial smart glove sensors to 10 million sets; ② In the public safety field, government procurement of bulletproof vest impact and firefighter vital sign monitoring sensors will grow at an annual rate of 20%, reaching a global shipment volume of 5 million sets by 2030.
(3) Consumer-grade wearable sensors: The CAGR is expected to reach 14.2%, and the scale will exceed 12 billion USD by 2030. The growth highlight lies in "functional upgrades": ① Multi-modal fusion sensors: The "five-in-one" sensor module integrating heart rate, blood oxygen, pressure, body temperature, and ECG will see its adoption rate in smart watches increase from 25% in 2025 to 60% in 2030; ② Metaverse-related sensors: Such as eye-tracking sensors and gesture recognition sensors for VR/AR devices. The global shipment volume will increase from 30 million units in 2025 to 180 million units in 2030, with a CAGR of 42%; ③ Smart clothing sensors: Such as ski suits integrating temperature regulation sensors and sports clothes with heart rate monitoring. The market scale will increase from 500 million USD in 2025 to 2 billion USD in 2030, benefiting from the growth of the outdoor sports population (globally expected to increase from 450 million in 2025 to 600 million in 2030).
2. Regional Market Growth Predictions:
China will continue to maintain the fastest growth rate (CAGR 22.1%). By 2030, the proportion of the Chinese market size in the world will increase from 27.3% in 2025 to 33.5%, mainly benefiting from: ① New medical infrastructure (5,000 community elderly care service centers will be added domestically from 2025 to 2029, driving the demand for home medical sensors); ② Industrial Internet investment (the scale of the core industrial Internet industry in China will reach 1.2 trillion RMB in 2025, and is expected to reach 3 trillion RMB in 2030, driving industrial sensor procurement); ③ Consumer electronics innovation (manufacturers such as Huawei and Xiaomi have launched an "all-scenario smart wearable ecosystem," combining sensors with smart homes and automotive interconnection, increasing the frequency of user device replacement).
The North American market (CAGR 17.8%) will remain the core market for medical-grade sensors; the European market (CAGR 16.5%) focuses on industrial safety and environmental protection-related sensors (such as wearable VOC detection sensors); the Southeast Asian market (CAGR 20.3%) benefits from the transfer of consumer electronics OEM and manufacturing upgrading, becoming a new growth pole.
3. Core Challenges and Development Suggestions:
(1) Technical bottlenecks: The mainstream level of the MARD value for high-end medical-grade sensors (such as non-invasive blood glucose) is currently 7%-8%, which still needs to be further reduced to below 5% to meet higher clinical needs. The mainstream protection level of industrial sensors is IP67+IK8, and its protection level (target IP68+IK10) and anti-electromagnetic interference capabilities need to be further improved. It is recommended that domestic enterprises increase R&D investment (the average R&D investment proportion of domestic sensor enterprises in 2025 is 5.8%, lower than the over 10% of international leaders), and strengthen cooperation with universities and hospitals (for example, Nuoa Medical cooperated with Tsinghua University to develop enzyme immobilization technology, shortening the R&D cycle by 30%).
(2) Supply chain security: High-end materials (such as medical-grade nano-gold particles) and MEMS foundry equipment (such as deep reactive ion etching machines) rely on imports. It is recommended to support upstream material enterprises through "domestic substitution special projects," and promote foundries such as SMIC and Hua Hong Semiconductor to upgrade MEMS production lines (such as increasing the capacity of 8-inch MEMS production lines to over 100,000 wafers per month).
(3) Market competition: Domestic enterprises face price wars in the consumer-grade sensor field (the average price of domestic heart rate sensors in 2025 is 30% lower than international brands). It is recommended to transform towards "high-end + differentiation." For example, AAC Technologies focuses on ultra-thin pressure sensors, avoiding direct competition with Bosch, and achieving a 40% market share in the smart bracelet segmented market.
Conclusion
As the core node connecting people, devices, and scenarios, wearable sensors are promoting intelligent transformation in fields such as consumer, medical, and industrial sectors through technological breakthroughs and scenario penetration. From the rapid expansion of market size to the continuous optimization of the competition pattern, from the cross-disciplinary fusion of technical mechanisms to the continuous extension of application scenarios, the wearable sensor industry has entered a new stage of development with "simultaneous improvement in quantity and quality."
In the future, with the continuous increase of policy support, the deep mining of user needs, and the autonomous and controllable supply chain, wearable sensors will not only be key tools for improving personal life quality, ensuring industrial safety production, and assisting medical health management, but will also become an important cornerstone supporting the implementation of national strategies such as the digital economy, intelligent manufacturing, and Healthy China, blooming with greater value in the intelligent era of the Internet of Everything.
Author | Guo Yuansheng, Deputy Director of the Science and Technology Committee of the Central Committee of the Jiusan Society, Executive Vice Chairman of the China Sensor and IoT Industry Alliance
Editor | Yang Pengyue Art Editor | Ma Liya Supervisor | Zhao Chen