Wireless sensor networks for healthcare: A survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Biofeedback data visualization for body sensor networks
Journal of Network and Computer Applications
Portable, non-invasive fall risk assessment in end stage renal disease patients on hemodialysis
WH '10 Wireless Health 2010
Longitudinal high-fidelity gait analysis with wireless inertial body sensors
WH '10 Wireless Health 2010
Analysis of gait in patients with normal pressure hydrocephalus
Proceedings of the First ACM Workshop on Mobile Systems, Applications, and Services for Healthcare
Continuous, non-invasive assessment of agitation in dementia using inertial body sensors
Proceedings of the 2nd Conference on Wireless Health
Enabling longitudinal assessment of ankle-foot orthosis efficacy for children with cerebral palsy
Proceedings of the 2nd Conference on Wireless Health
Grammar-based, posture- and context-cognitive detection for falls with different activity levels
Proceedings of the 2nd Conference on Wireless Health
Proceedings of the Fifth International Conference on Body Area Networks
Proceedings of the Fifth International Conference on Body Area Networks
Application-Focused Energy-Fidelity Scalability for Wireless Motion-Based Health Assessment
ACM Transactions on Embedded Computing Systems (TECS) - Special Section on CAPA'09, Special Section on WHS'09, and Special Section VCPSS' 09
Optimizing battery lifetime-fidelity tradeoffs in BSNs using personal activity profiles
Proceedings of the 7th International Conference on Body Area Networks
Aiding diagnosis of normal pressure hydrocephalus with enhanced gait feature separability
Proceedings of the conference on Wireless Health
Characterising and minimising sources of error in inertial body sensor networks
International Journal of Autonomous and Adaptive Communications Systems
WBAN Based Long Term ECG Monitoring
International Journal of Monitoring and Surveillance Technologies Research
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This work presents TEMPO (Technology-Enabled Medical Precision Observation) 3.1, a third generation body area sensor platform that accurately and precisely captures, processes, and wirelessly transmits six-degrees-of-freedom inertial data in a wearable, non-invasive form factor. TEMPO 3.1 is designed to be usable to both the wearer and researcher, thereby enabling motion capture applications in body area sensor networks (BASNs). A complete system is designed and developed that includes the following: (1) enabling technologies and hardware design of TEMPO 3.1, (2) a custom real-time operating system (TEMPOS) that manages all aspects of signal acquisition, signal processing, data management, peripheral control, and wireless communication on a TEMPO node, and (3) a custom case design. The system is evaluated and compared to existing BASN hardware platforms. TEMPO 3.1 creates new opportunities for wearable, continuous monitoring applications and extends the research space of current efforts.