Skip to main content

On-body Sensing Systems: Motion Capture for Health Monitoring.

Haratian, R., 2021. On-body Sensing Systems: Motion Capture for Health Monitoring. In: Seventeenth International Conference on Condition Monitoring and Asset Management (CM2021): The Future of Condition Monitoring, 14-18 June 2021, London (Virtual).

Full text available as:

[img]
Preview
PDF
4A1.Haratian.Roya.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial.

369kB

Official URL: https://www.bindt.org/events/CM-2021/

Abstract

On-body sensors capture quantitative data from variety of bio-signals on a subject’s body with applications in health, sports and entertainment. With the increase in health costs, a need has arisen to monitor a patient’s condition out of hospital in a costeffective way. In healthcare applications on-body sensing systems can provide feedback information about one’s health condition either to the user or to a medical centre. They can also be used for managing and monitoring chronic disease, elderly people, and rehabilitation patients. In rehabilitation applications, such systems can be used to capture patient movement and monitor progress or provide feedback to enhance patients’ motor learning and increase rehabilitation effectiveness. Human motion capture systems are expected to generate motion data through several techniques that dynamically represent the posture changes of a human body based on motion sensor technologies. In motion analysis, the human body is typically modelled as a system of rigid links connected by rotary joints. In this paper after describing body models and their approximation by link-segment models, we introduce kinematics and inverse kinematics problems for determining motion. Different sensor technologies and related motion capture systems are then discussed. It is shown how motion data is derived from position and orientation for the different motion capture technologies.

Item Type:Conference or Workshop Item (Lecture)
Group:Faculty of Science & Technology
ID Code:36017
Deposited By: Symplectic RT2
Deposited On:16 Sep 2021 11:45
Last Modified:14 Mar 2022 14:29

Downloads

Downloads per month over past year

More statistics for this item...
Repository Staff Only -