Wearable Technology for Human Activity Monitoring and Recognition

2021 ◽  
pp. 191-218
Author(s):  
Shiban Kishen Koul ◽  
Richa Bharadwaj
Keyword(s):  
Human Activity ◽  
Wearable Technology ◽  
Activity Monitoring

scholarly journals Sport-Related Human Activity Detection and Recognition Using a Smartwatch

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 5001 ◽  
Author(s):  
Zhendong Zhuang ◽  
Yang Xue
Keyword(s):  
Human Activity ◽  
Recognition Task ◽  
Sliding Window ◽  
Research Field ◽  
Activity Monitoring ◽  
Activity Detection ◽  
Related Activity ◽  
Window Method ◽  
Human Activity Detection ◽  
Detection And Recognition

As an active research field, sport-related activity monitoring plays an important role in people’s lives and health. This is often viewed as a human activity recognition task in which a fixed-length sliding window is used to segment long-term activity signals. However, activities with complex motion states and non-periodicity can be better monitored if the monitoring algorithm is able to accurately detect the duration of meaningful motion states. However, this ability is lacking in the sliding window approach. In this study, we focused on two types of activities for sport-related activity monitoring, which we regard as a human activity detection and recognition task. For non-periodic activities, we propose an interval-based detection and recognition method. The proposed approach can accurately determine the duration of each target motion state by generating candidate intervals. For weak periodic activities, we propose a classification-based periodic matching method that uses periodic matching to segment the motion sate. Experimental results show that the proposed methods performed better than the sliding window method.

scholarly journals All-Printed Human Activity Monitoring and Energy Harvesting Device for Internet of Thing Applications

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1197 ◽  
Author(s):  
Shawkat Ali ◽  
Saleem Khan ◽  
Amine Bermak
Keyword(s):  
Energy Harvesting ◽  
Human Activity ◽  
Indium Tin Oxide ◽  
Activity Monitoring ◽  
The Self ◽  
Smart Device ◽  
Bridge Rectifier ◽  
Self Powered ◽  
Iot Devices ◽  
Human Activity Detection

A self-powered device for human activity monitoring and energy harvesting for Internet of Things (IoT) devices is proposed. The self-powered device utilizes flexible Nano-generators (NGs), flexible diodes and off-the-shelf capacitors. During footsteps the NGs generate an AC voltage then it is converted into DC using rectifiers and the DC power is stored in a capacitor for powering the IoT devices. Polydimethylsiloxane (PDMS) and zinc stannate (ZnSnO3) composite is utilized for the NG active layer, indium tin oxide (ITO) and aluminum (Al) are used as the bottom and top electrodes, respectively. Four diodes are fabricated on the bottom electrode of the NG and connected in bridge rectifier configuration. A generated voltage of 18 Vpeak was achieved with a human footstep. The self-powered smart device also showed excellent robustness and stable energy scavenger from human footsteps. As an application we demonstrate human activity detection and energy harvesting for IoT devices.

Highly sensitive and multifunctional piezoresistive sensor based on polyaniline foam for wearable Human-Activity monitoring

2019 ◽  
Vol 121 ◽  
pp. 510-516 ◽  
Author(s):  
Shaodi Zheng ◽  
Xiaotian Wu ◽  
Yanhao Huang ◽  
Zewang Xu ◽  
Wei Yang ◽  
...  
Keyword(s):  
Human Activity ◽  
Activity Monitoring ◽  
Piezoresistive Sensor ◽  
Highly Sensitive

Human activity monitoring based on hidden Markov models using a smartphone

2016 ◽  
Vol 19 (6) ◽  
pp. 27-31 ◽  
Author(s):  
Ruben San-Segundo ◽  
Julian Echeverry-Correa ◽  
Christian Salamea ◽  
Jose Manuel Pardo
Keyword(s):  
Hidden Markov Models ◽  
Human Activity ◽  
Markov Models ◽  
Hidden Markov ◽  
Activity Monitoring

Micro Doppler Radar and Depth Sensor Fusion for Human Activity Monitoring in AAL

2019 ◽  
pp. 519-528
Author(s):  
Susanna Spinsante ◽  
Matteo Pepa ◽  
Stefano Pirani ◽  
Ennio Gambi ◽  
Francesco Fioranelli
Keyword(s):  
Sensor Fusion ◽  
Human Activity ◽  
Doppler Radar ◽  
Activity Monitoring ◽  
Depth Sensor
Sign in / Sign up

Export Citation Format

Share Document