Lower Limb Wearable Capacitive Sensing and Its Applications to Recognizing Human Gaits

Overview

Journal Sensors (Basel)

Publisher MDPI

Specialty Biotechnology

Date 2013 Oct 3

PMID 24084122

Citations 6

Authors

Enhao Zheng

Baojun Chen

Kunlin Wei

Qining Wang

Affiliations

Soon will be listed here.

Abstract

In this paper, we present an approach to sense human body capacitance and apply it to recognize lower limb locomotion modes. The proposed wearable sensing system includes sensing bands, a signal processing circuit and a gait event detection module. Experiments on long-term working stability, adaptability to disturbance and locomotion mode recognition are carried out to validate the effectiveness of the proposed approach. Twelve able-bodied subjects are recruited, and eleven normal gait modes are investigated. With an event-dependent linear discriminant analysis classifier and feature selection procedure, four time-domain features are used for pattern recognition and satisfactory recognition accuracies (97:3% ± 0:5%, 97:0% ± 0:4%, 95:6% ± 0:9% and 97:0% ± 0:4% for four phases of one gait cycle respectively) are obtained. The accuracies are comparable with that from electromyography-based systems and inertial-based systems. The results validate the effectiveness of the proposed lower limb capacitive sensing approach in recognizing human normal gaits.

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References

Au S, Berniker M, Herr H . Powered ankle-foot prosthesis to assist level-ground and stair-descent gaits. Neural Netw. 2008; 21(4):654-66. DOI: 10.1016/j.neunet.2008.03.006. View

Peng G, Bocko M . Non-contact ECG sensing employing gradiometer electrodes. IEEE Trans Biomed Eng. 2012; 60(1):179-83. PMC: 3540983. DOI: 10.1109/TBME.2012.2219531. View

Dai C, Lu P, Chang C, Liu C . Capacitive micro pressure sensor integrated with a ring oscillator circuit on chip. Sensors (Basel). 2012; 9(12):10158-70. PMC: 3267215. DOI: 10.3390/s91210158. View

Peeraer L, Aeyels B, Van der Perre G . Development of EMG-based mode and intent recognition algorithms for a computer-controlled above-knee prosthesis. J Biomed Eng. 1990; 12(3):178-82. DOI: 10.1016/0141-5425(90)90037-n. View

Franz J, Paylo K, Dicharry J, Riley P, Kerrigan D . Changes in the coordination of hip and pelvis kinematics with mode of locomotion. Gait Posture. 2009; 29(3):494-8. DOI: 10.1016/j.gaitpost.2008.11.011. View

Atallah L, Lo B, Ali R, King R, Yang G . Real-time activity classification using ambient and wearable sensors. IEEE Trans Inf Technol Biomed. 2009; 13(6):1031-9. DOI: 10.1109/TITB.2009.2028575. View

Wang F, Marashdeh Q, Fan L, Warsito W . Electrical capacitance volume tomography: design and applications. Sensors (Basel). 2012; 10(3):1890-917. PMC: 3264458. DOI: 10.3390/s100301890. View

Hargrove L, Li G, Englehart K, Hudgins B . Principal components analysis preprocessing for improved classification accuracies in pattern-recognition-based myoelectric control. IEEE Trans Biomed Eng. 2009; 56(5):1407-14. DOI: 10.1109/TBME.2008.2008171. View

Karantonis D, Narayanan M, Mathie M, Lovell N, Celler B . Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring. IEEE Trans Inf Technol Biomed. 2006; 10(1):156-67. DOI: 10.1109/titb.2005.856864. View

10.

Huang H, Kuiken T, Lipschutz R . A strategy for identifying locomotion modes using surface electromyography. IEEE Trans Biomed Eng. 2009; 56(1):65-73. PMC: 3025288. DOI: 10.1109/TBME.2008.2003293. View

11.

Ohhashi T, Sakaguchi M, Tsuda T . Human perspiration measurement. Physiol Meas. 1998; 19(4):449-61. DOI: 10.1088/0967-3334/19/4/001. View

12.

Chen B, Zheng E, Fan X, Liang T, Wang Q, Wei K . Locomotion mode classification using a wearable capacitive sensing system. IEEE Trans Neural Syst Rehabil Eng. 2013; 21(5):744-55. DOI: 10.1109/TNSRE.2013.2262952. View

13.

Bunderson N, Kuiken T . Quantification of feature space changes with experience during electromyogram pattern recognition control. IEEE Trans Neural Syst Rehabil Eng. 2012; 20(3):239-46. DOI: 10.1109/TNSRE.2011.2182525. View

14.

Oehler M, Ling V, Melhorn K, Schilling M . A multichannel portable ECG system with capacitive sensors. Physiol Meas. 2008; 29(7):783-93. DOI: 10.1088/0967-3334/29/7/007. View

15.

Susi M, Renaudin V, Lachapelle G . Motion mode recognition and step detection algorithms for mobile phone users. Sensors (Basel). 2013; 13(2):1539-62. PMC: 3649428. DOI: 10.3390/s130201539. View

16.

Ueno A, Akabane Y, Kato T, Hoshino H, Kataoka S, Ishiyama Y . Capacitive sensing of electrocardiographic potential through cloth from the dorsal surface of the body in a supine position: a preliminary study. IEEE Trans Biomed Eng. 2007; 54(4):759-66. DOI: 10.1109/TBME.2006.889201. View

17.

Cheng M, Lin C, Lai Y, Yang Y . A polymer-based capacitive sensing array for normal and shear force measurement. Sensors (Basel). 2011; 10(11):10211-25. PMC: 3230994. DOI: 10.3390/s101110211. View

18.

Presacco A, Forrester L, L Contreras-Vidal J . Decoding intra-limb and inter-limb kinematics during treadmill walking from scalp electroencephalographic (EEG) signals. IEEE Trans Neural Syst Rehabil Eng. 2012; 20(2):212-9. PMC: 3355189. DOI: 10.1109/TNSRE.2012.2188304. View