Sensor-Based Wearable Systems for Monitoring Human Motion and Posture: A Review

Overview

Journal Sensors (Basel)

Publisher MDPI

Specialty Biotechnology

Date 2023 Nov 25

PMID 38005436

Authors

Xinxin Huang

Yunan Xue

Shuyun Ren

Fei Wang

Affiliations

Soon will be listed here.

Abstract

In recent years, marked progress has been made in wearable technology for human motion and posture recognition in the areas of assisted training, medical health, VR/AR, etc. This paper systematically reviews the status quo of wearable sensing systems for human motion capture and posture recognition from three aspects, which are monitoring indicators, sensors, and system design. In particular, it summarizes the monitoring indicators closely related to human posture changes, such as trunk, joints, and limbs, and analyzes in detail the types, numbers, locations, installation methods, and advantages and disadvantages of sensors in different monitoring systems. Finally, it is concluded that future research in this area will emphasize monitoring accuracy, data security, wearing comfort, and durability. This review provides a reference for the future development of wearable sensing systems for human motion capture.

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References

Eom J, Jaisutti R, Lee H, Lee W, Heo J, Lee J . Highly Sensitive Textile Strain Sensors and Wireless User-Interface Devices Using All-Polymeric Conducting Fibers. ACS Appl Mater Interfaces. 2017; 9(11):10190-10197. DOI: 10.1021/acsami.7b01771. View

Wang Z, Huang Y, Sun J, Huang Y, Hu H, Jiang R . Polyurethane/Cotton/Carbon Nanotubes Core-Spun Yarn as High Reliability Stretchable Strain Sensor for Human Motion Detection. ACS Appl Mater Interfaces. 2016; 8(37):24837-43. DOI: 10.1021/acsami.6b08207. View

Ryu S, Lee P, Chou J, Xu R, Zhao R, Hart A . Extremely Elastic Wearable Carbon Nanotube Fiber Strain Sensor for Monitoring of Human Motion. ACS Nano. 2015; 9(6):5929-36. DOI: 10.1021/acsnano.5b00599. View

Taffoni F, Focaroli V, Formica D, Gugliemelli E, Keller F, Iverson J . Sensor-based technology in the study of motor skills in infants at risk for ASD. Proc IEEE RAS EMBS Int Conf Biomed Robot Biomechatron. 2014; :1879-1883. PMC: 4105205. DOI: 10.1109/BioRob.2012.6290922. View

Gao Q, Sun F, Li Y, Li L, Liu M, Wang S . Biological Tissue-Inspired Ultrasoft, Ultrathin, and Mechanically Enhanced Microfiber Composite Hydrogel for Flexible Bioelectronics. Nanomicro Lett. 2023; 15(1):139. PMC: 10225432. DOI: 10.1007/s40820-023-01096-4. View

Servati A, Zou L, Jane Wang Z, Ko F, Servati P . Novel Flexible Wearable Sensor Materials and Signal Processing for Vital Sign and Human Activity Monitoring. Sensors (Basel). 2017; 17(7). PMC: 5539541. DOI: 10.3390/s17071622. View

Wilharm A, Hurschler C, Dermitas T, Bohnsack M . Use of Tekscan K-scan sensors for retropatellar pressure measurement avoiding errors during implantation and the effects of shear forces on the measurement precision. Biomed Res Int. 2013; 2013:829171. PMC: 3866885. DOI: 10.1155/2013/829171. View

Yamada T, Hayamizu Y, Yamamoto Y, Yomogida Y, Izadi-Najafabadi A, Futaba D . A stretchable carbon nanotube strain sensor for human-motion detection. Nat Nanotechnol. 2011; 6(5):296-301. DOI: 10.1038/nnano.2011.36. View

Yuan W, Zhou Q, Li Y, Shi G . Small and light strain sensors based on graphene coated human hairs. Nanoscale. 2015; 7(39):16361-5. DOI: 10.1039/c5nr04312c. View

10.

Zhang M, Wang C, Wang Q, Jian M, Zhang Y . Sheath-Core Graphite/Silk Fiber Made by Dry-Meyer-Rod-Coating for Wearable Strain Sensors. ACS Appl Mater Interfaces. 2016; 8(32):20894-9. DOI: 10.1021/acsami.6b06984. View

11.

Chiang C, Chen K, Liu K, Hsu S, Chan C . Data Collection and Analysis Using Wearable Sensors for Monitoring Knee Range of Motion after Total Knee Arthroplasty. Sensors (Basel). 2017; 17(2). PMC: 5336055. DOI: 10.3390/s17020418. View

12.

Zhou J, Gu Y, Fei P, Mai W, Gao Y, Yang R . Flexible piezotronic strain sensor. Nano Lett. 2008; 8(9):3035-40. DOI: 10.1021/nl802367t. View

13.

Li J, Yin J, Wee M, Chinnappan A, Ramakrishna S . A Self-Powered Piezoelectric Nanofibrous Membrane as Wearable Tactile Sensor for Human Body Motion Monitoring and Recognition. Adv Fiber Mater. 2023; :1-14. PMC: 10088646. DOI: 10.1007/s42765-023-00282-8. View

14.

Khan A, Lee Y, Lee S, Kim T . Accelerometer's position independent physical activity recognition system for long-term activity monitoring in the elderly. Med Biol Eng Comput. 2010; 48(12):1271-9. DOI: 10.1007/s11517-010-0701-3. View

15.

Yan C, Wang J, Kang W, Cui M, Wang X, Foo C . Highly stretchable piezoresistive graphene-nanocellulose nanopaper for strain sensors. Adv Mater. 2013; 26(13):2022-7. DOI: 10.1002/adma.201304742. View

16.

Farooq M, Chandler-Laney P, Hernandez-Reif M, Sazonov E . Monitoring of infant feeding behavior using a jaw motion sensor. J Healthc Eng. 2015; 6(1):23-40. PMC: 4752004. DOI: 10.1260/2040-2295.6.1.23. View

17.

Kwak S, Yoo S, Avila R, Chung H, Jeong H, Liu C . Skin-Integrated Devices with Soft, Holey Architectures for Wireless Physiological Monitoring, With Applications in the Neonatal Intensive Care Unit. Adv Mater. 2021; 33(44):e2103974. DOI: 10.1002/adma.202103974. View

18.

De Brabandere A, Emmerzaal J, Timmermans A, Jonkers I, Vanwanseele B, Davis J . A Machine Learning Approach to Estimate Hip and Knee Joint Loading Using a Mobile Phone-Embedded IMU. Front Bioeng Biotechnol. 2020; 8:320. PMC: 7174587. DOI: 10.3389/fbioe.2020.00320. View

19.

Smith B, Trujillo-Priego I, Lane C, Finley J, Horak F . Daily Quantity of Infant Leg Movement: Wearable Sensor Algorithm and Relationship to Walking Onset. Sensors (Basel). 2015; 15(8):19006-20. PMC: 4570357. DOI: 10.3390/s150819006. View

20.

Lockman J, Fisher R, Olson D . Detection of seizure-like movements using a wrist accelerometer. Epilepsy Behav. 2011; 20(4):638-41. DOI: 10.1016/j.yebeh.2011.01.019. View