Academic Journal
Multimodal hand gesture recognition using single IMU and acoustic measurements at wrist.
| Τίτλος: | Multimodal hand gesture recognition using single IMU and acoustic measurements at wrist. |
|---|---|
| Συγγραφείς: | Siddiqui N; Department of Electrical Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China., Chan RHM; Department of Electrical Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China. |
| Πηγή: | PloS one [PLoS One] 2020 Jan 13; Vol. 15 (1), pp. e0227039. Date of Electronic Publication: 2020 Jan 13 (Print Publication: 2020). |
| Τύπος έκδοσης: | Journal Article; Research Support, Non-U.S. Gov't |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: San Francisco, CA : Public Library of Science |
| Ιατρικοί όροι (MeSH): | Acoustics* , Gestures* , Pattern Recognition, Physiological* , Wearable Electronic Devices*, Hand/*physiology , Wrist Joint/*physiology, Adult ; Female ; Humans ; Male ; Movement ; Young Adult |
| Περίληψη: | To facilitate hand gesture recognition, we investigated the use of acoustic signals with an accelerometer and gyroscope at the human wrist. As a proof-of-concept, the prototype consisted of 10 microphone units in contact with the skin placed around the wrist along with an inertial measurement unit (IMU). The gesture recognition performance was evaluated through the identification of 13 gestures used in daily life. The optimal area for acoustic sensor placement at the wrist was examined using the minimum redundancy and maximum relevance feature selection algorithm. We recruited 10 subjects to perform over 10 trials for each set of hand gestures. The accuracy was 75% for a general model with the top 25 features selected, and the intra-subject average classification accuracy was over 80% with the same features using one microphone unit at the mid-anterior wrist and an IMU. These results indicate that acoustic signatures from the human wrist can aid IMU sensing for hand gesture recognition, and the selection of a few common features for all subjects could help with building a general model. The proposed multimodal framework helps address the single IMU sensing bottleneck for hand gestures during arm movement and/or locomotion. |
| Competing Interests: | The authors have declared that no competing interests exist. |
| References: | IEEE Trans Neural Syst Rehabil Eng. 2019 Apr;27(4):724-732. (PMID: 30892217) J Electromyogr Kinesiol. 1992;2(3):141-9. (PMID: 20719607) J Biomech. 1996 Apr;29(4):475-81. (PMID: 8964777) Conf Proc IEEE Eng Med Biol Soc. 2017 Jul;2017:4443-4446. (PMID: 29060883) Clin Physiol Funct Imaging. 2018 Mar;38(2):312-325. (PMID: 28251802) Cell Syst. 2017 Nov 22;5(5):527-531.e3. (PMID: 29102608) IEEE Trans Neural Netw. 2009 Feb;20(2):189-201. (PMID: 19150792) Sci Adv. 2016 Nov 16;2(11):e1601185. (PMID: 28138529) J Physiol Anthropol. 2008 Jan;27(1):33-42. (PMID: 18239348) Biomed Eng Online. 2005 Dec 19;4:67. (PMID: 16364182) Med Biol Eng Comput. 2001 Mar;39(2):195-201. (PMID: 11361247) Sensors (Basel). 2018 Aug 22;18(9):null. (PMID: 30135413) J Electromyogr Kinesiol. 2000 Oct;10(5):361-74. (PMID: 11018445) Eur J Appl Physiol Occup Physiol. 1989;58(5):528-33. (PMID: 2759079) |
| Entry Date(s): | Date Created: 20200114 Date Completed: 20200420 Latest Revision: 20200420 |
| Update Code: | 20260130 |
| PubMed Central ID: | PMC6957149 |
| DOI: | 10.1371/journal.pone.0227039 |
| PMID: | 31929544 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1932-6203 |
|---|---|
| DOI: | 10.1371/journal.pone.0227039 |