Gesture Based Help Identification for Hospital & ElderlyCare Using Dynamic Time Warping: A Systematic Study
Authors: 
Ahmad Sufril Azlan Mohamed, Effha Binti Soter, Anand Singh, Nur Intan Raihana RuhaiyemAuthors Info & Claims
Ahmad Sufril Azlan Mohamed, Effha Binti Soter, Anand Singh, Nur Intan Raihana RuhaiyemAuthors Info & ClaimsPages 94 - 98
Abstract
Recent advancement of depth imaging sensor technology can provide opportunities, especially in healthcare sector to improve the quality of life of the hospital patients and elderly care institutes by facilitating certain tasks without any assistant and enabling supportive ecosphere. This paper presents a novel hand gesture system via motion capture for appliance control in the hospital environment. A selection of hand gestures were prepared for the subject to perform with a set of questionnaires to learn the user acceptance towards this implementation with the adoption of dynamic time warping (DTW) algorithm for identifying the gestures. The results shown that gestures are easily performed by the patient to control specific tasks in a controlled environment. Most participants agreed that this system is easy to use and learn. The aim of this study is to evaluate the user experience on the proposed gesture setup and study the acceptance of the proposed hand gestures by the subjects.
References
[1]
Ahuja, M. K. and Singh, A. 2015. Static vision based hand gesture recognition using principal component analysis. IEEE 3rd International Conference on MOOCs. Innovation and Technology in Education (MITE), (October 1-2, 2015).
[2]
Ann., O. C. and Theng, L. B. 2014. Human activity recognition: A review. IEEE International Conference on Control System, Computing and Engineering. (November 28-30, 2014), 389--393.
[3]
Argoty, J. A., Figueroa, P.2014. Design and development of a prototype of an interactive hospital room with kinect. Proceedings of the 15th International Conference on Human Interaction. (Spain, September 10-12, 2014).
[4]
Athavale, S. and Deshmukh, M. 2014. Dynamic hand gesture recognition for human computer interaction: A comparative study. International J. of Engineering Research and General Science. 2, 2(February -- March, 2014), 38--55.
[5]
Bharambe, A., Chanekar, D., Naik, D. and Vitekar, A. B. Automatic hand gesture based remote control for home appliances. International J. of Advanced Research in Computer Science and Software Engineering.5, 2 (2015), 567--571.
[6]
Bonechere, B., Jansen, B., Salvia, P., Bouzahouene, H., Omelina, L., Cornelis, J., Rooze, M. and Jan, S. V. S. Can the Kinect sensors be used for motion analysis? Trans. On Electrical and Electronic Circuits and Systems. 4,1(2014), 1--6.
[7]
Chen, Z. H., Kim, J. T., Liang, J., Zhang, J. and Yuan, Y. B. Real-time hand gesture recognition using finger segmentation. The Scientific World J., 2014.
[8]
Dan, R. B. and Mohod, P. S. Survey on hand gesture recognition approaches. International J. of Computer Science and Information Technologies. 5, 2 (2012), 2050--2052.
[9]
Ganzeboom, M. How hand gestures are recognized using data glove. In Human Media Interaction (HMI). 2010.
[10]
Hernandez, J., Mcduff, D.J. and Picard, R.W. 2015. Bioinsights Extracting personal data from "Still" wearable motion sensors. In Proceeding IEEE 12th International Conference Wearable Implantable Body Sensor Network. (June 9-12, 2015).
[11]
Jacob, M. G., Li, Y. T., Akingba, G. A. and Wachs. 2013.Collaboration with a robotic scrub nurse.Commun. ACM, 56, 5(May. 2013), 68--75.
[12]
Jyothilakshmi, P., Rekha, K. R., and Natraj, K. R. Implementation of a smart ward system in a hi-tech hospital by using a kinect sensor camera. International J. on Recent and Innovation Trends in Computing and Comun., 4, 5 (2016), 531--536.
[13]
Jyothilakshmi, P., Rekha, K. R., and Natraj, K. R. Patient assistance system in a super specialty hospital using a kinect sensor camera 2016. International Conference on Electrical, Electronics, and Optimization Techniques. (March 3-5, 2016).
[14]
Kelly, P., Marshall, S. J., Badland, H., Kerr, J., Oliver, M., Doherthy, A. R. and Foster, C. An ethical framework for automated, wearable cameras in health behavior research. American J. of preventive medicine. 44 (2013), 314--319.
[15]
Kumar, P., Verma, J. and Prasad, S. 2012. Hand data glove: A wearable real-time device for human computer interaction. International J. of Advanced Science and Technology. 43(June, 2012), 15--26.
[16]
Murthy, G. R. S. and Jadon, R. S. 2009. A review of vision based hand gestures recognition. International J. of Information Technology and Knowledge Management. 12,2 (July-December, 2009), 405--410.
[17]
Ni, B., Da, N. C. and Moulin, P. RGBD-camera based get-up event detection for hospital fall prevention. In Proceedings of International Conference on Acoustics, Speech, and Signal Process. (2000), 1405--1408.
[18]
Ren, Z., Yuan, J. and Zhang Z. Robust hand gesture recognition based on finger-earth mover's distance with a commodity depth camera. In Proceedings of the 19thInternational Conference on Multimedia, ACM. (2011), 1093--1096.
[19]
Riemen, R. The sensors behind the apple watch. Electrical Engineering Community. 2015.
[20]
Rosli, L. 2016. What happens when Malaysia enters ageing nation status in 2030? New Straits Times Press (M) Berhad (10 January 2018).
[21]
Samad, S. A. and Mansor, N. 2013. Population ageing and social protection in Malaysia. Malaysia J. of Economic Studies. 139--156.
[22]
Solanki, U. V. and Desai, N. Hand gesture based remote control for home appliances: Handmote. World Congress on Information and Commun. Technologies. (2011), 419--423.
[23]
Sonkusare, J. S., Chopade, N. B., Sor, R. and Tade, S. L. 2015. A review on hand gesture recognition system. International Conference on Computing Communication Control and Automation, (February 26-27, 2015).
[24]
Wachs, J. P., Kolsch, M., Stern, H. and Edan, Y. 2011. Vision- based hand gesture applications. ACM Commun. 54,2 (February, 2011), 60--71.
[25]
Weng, C., Li, Y., Zhang, M., Guo, K., Tang, X., Pan, Z. Robust hand posture recognition integrating multi-cue hand tracking. International Conference on Technologies for E-learning and Digital Entertainment. 6249 (2010), 497--508.
Index Terms
- Gesture Based Help Identification for Hospital & ElderlyCare Using Dynamic Time Warping: A Systematic Study
Recommendations
Smart Hand Device Gesture Recognition with Dynamic Time-Warping Method
BDIOT '17: Proceedings of the International Conference on Big Data and Internet of ThingIn this paper, we present a smart wearable hand-gesture recognition system based on the movement of the hand and fingers. The proposed smart wearable system is built using the fewest sensors necessary for gesture recognition. Thus, motion sensors are ...
Robust gesture recognition using feature pre-processing and weighted dynamic time warping
Gesture recognition is a technology often used in human-computer interaction applications. Dynamic time warping (DTW) is one of the techniques used in gesture recognition to find an optimal alignment between two sequences. Oftentimes a pre-processing of ...
Human-Machine Interaction based on Hand Gesture Recognition using Skeleton Information of Kinect Sensor
ICAIT'2018: Proceedings of the 3rd International Conference on Applications in Information TechnologyThe hand gesture provides a natural and intuitive communication medium for the human and machine interaction. Because, it can use in virtual reality, language detection, computer games, and other human-computer or human-machine instruction applications. ...
Comments
Information & Contributors
Information
Published In
December 2017
272 pages
ISBN:9781450353830
DOI:10.1145/3177404
Copyright © 2017 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
In-Cooperation
- Nanyang Technological University
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 27 December 2017
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Funding Sources
- Universiti Sains Malaysia
Conference
ICVIP 2017
ICVIP 2017: International Conference on Video and Image Processing
December 27 - 29, 2017
Singapore, Singapore
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 90Total Downloads
- Downloads (Last 12 months)3
- Downloads (Last 6 weeks)0
Reflects downloads up to 14 Sep 2024
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in