Wearable sensor networks for human gait

2019 ◽  
pp. 321-360
Author(s):  
José Machado da Silva ◽  
Fardin Derogarian ◽  
João Canas Ferreira ◽  
Vítor Grade Tavares
Keyword(s):  
Sensor Networks ◽  
Human Gait ◽  
Wearable Sensor

scholarly journals Energy-aware activity classification using wearable sensor networks

2013 ◽  
Author(s):  
Bo Dong ◽  
Alexander Montoye ◽  
Rebecca Moore ◽  
Karin Pfeiffer ◽  
Subir Biswas
Keyword(s):  
Sensor Networks ◽  
Wearable Sensor ◽  
Activity Classification ◽  
Energy Aware

Wearable sensor networks: A measurement study

2020 ◽  
Author(s):  
Armir Bujari ◽  
Ombretta Gaggi ◽  
Claudio E. Palazzi ◽  
Giacomo Quadrio
Keyword(s):  
Sensor Networks ◽  
Wearable Sensor ◽  
Measurement Study

Power-Aware Computing in Wearable Sensor Networks: An Optimal Feature Selection

2015 ◽  
Vol 14 (4) ◽  
pp. 800-812 ◽  
Author(s):  
Hassan Ghasemzadeh ◽  
Navid Amini ◽  
Ramyar Saeedi ◽  
Majid Sarrafzadeh
Keyword(s):  
Feature Selection ◽  
Sensor Networks ◽  
Wearable Sensor ◽  
Optimal Feature Selection ◽  
Optimal Feature

Body-posture-based dynamic link power control in wearable sensor networks

2010 ◽  
Vol 48 (7) ◽  
pp. 134-142 ◽  
Author(s):  
Muhannad Quwaider ◽  
Jayanthi Rao ◽  
Subir Biswas
Keyword(s):  
Sensor Networks ◽  
Power Control ◽  
Body Posture ◽  
Wearable Sensor ◽  
Dynamic Link

scholarly journals A Real-Time Cardiac Arrhythmia Classification System with Wearable Sensor Networks

Sensors ◽  
2012 ◽  
Vol 12 (9) ◽  
pp. 12844-12869 ◽  
Author(s):  
Sheng Hu ◽  
Hongxing Wei ◽  
Youdong Chen ◽  
Jindong Tan
Keyword(s):  
Sensor Networks ◽  
Real Time ◽  
Cardiac Arrhythmia ◽  
Classification System ◽  
Wearable Sensor

scholarly journals Classifier-Based Data Transmission Reduction in Wearable Sensor Network for Human Activity Monitoring

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 85
Author(s):  
Marcin Lewandowski ◽  
Bartłomiej Płaczek ◽  
Marcin Bernas
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
Activity Recognition ◽  
Human Activity ◽  
Network Lifetime ◽  
Data Transmission ◽  
Activity Monitoring ◽  
Sensor Nodes ◽  
Wearable Sensor ◽  
Transmission Reduction

The recent development of wireless wearable sensor networks offers a spectrum of new applications in fields of healthcare, medicine, activity monitoring, sport, safety, human-machine interfacing, and beyond. Successful use of this technology depends on lifetime of the battery-powered sensor nodes. This paper presents a new method for extending the lifetime of the wearable sensor networks by avoiding unnecessary data transmissions. The introduced method is based on embedded classifiers that allow sensor nodes to decide if current sensor readings have to be transmitted to cluster head or not. In order to train the classifiers, a procedure was elaborated, which takes into account the impact of data selection on accuracy of a recognition system. This approach was implemented in a prototype of wearable sensor network for human activity monitoring. Real-world experiments were conducted to evaluate the new method in terms of network lifetime, energy consumption, and accuracy of human activity recognition. Results of the experimental evaluation have confirmed that, the proposed method enables significant prolongation of the network lifetime, while preserving high accuracy of the activity recognition. The experiments have also revealed advantages of the method in comparison with state-of-the-art algorithms for data transmission reduction.

A DIY approach to wearable sensor networks

2021 ◽  
Author(s):  
Rongzhou Lin ◽  
John S. Ho
Keyword(s):  
Sensor Networks ◽  
Wearable Sensor
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