Shoulder and Trunk Posture Monitoring System Over Time for Seating Persons

2021 ◽  
pp. 250-260
Author(s):  
Ferdews Tlili ◽  
Rim Haddad ◽  
Ridha Bouallegue ◽  
Raed Shubair
Keyword(s):  
Monitoring System ◽  
Trunk Posture ◽  
Posture Monitoring ◽  
Over Time

A Real-time Posture Monitoring System Towards Bad Posture Detection

2021 ◽  
Author(s):  
Ferdews Tlili ◽  
Rim Haddad ◽  
Ridha Bouallegue ◽  
Neila Mezghani
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Posture Monitoring

scholarly journals Android Based Low Cost Sitting Posture Monitoring System

2020 ◽  
Author(s):  
Nusrat Binta Nizam ◽  
Tohfatul Jinan ◽  
Wahida Binte Naz Aurthy ◽  
Md. Rakib Hossen ◽  
Jahid Ferdous
Keyword(s):  
Monitoring System ◽  
Low Cost ◽  
Sitting Posture ◽  
Posture Monitoring

Execution Process Monitoring for Ship Curved Block Construction Based on Task Package and Workload Distribution Sheet

2013 ◽  
Vol 711 ◽  
pp. 602-607
Author(s):  
Da Ming Pei ◽  
Li Rui Wang ◽  
Qi Jin Tang
Keyword(s):  
Data Collection ◽  
Monitoring System ◽  
Process Monitoring ◽  
Top Down ◽  
Monitoring Technique ◽  
Vector Projection ◽  
Work Distribution ◽  
Block Construction ◽  
Workload Distribution ◽  
Over Time

Aiming at the demands of top-down task transmission and bottom-up status coordination in the execution of ship curved block construction, a hierarchical execution process monitoring technique considering workplace, curved block, task package (TP) and workload distribution sheet (WDS) was put forward. Adopting linear fitting and graphics epitaxy, the plane vector projection modeling for ship curved block was achieved. Based on visualized monitoring technology for curved blocks evolution over time in workplace, a hierarchical execution process monitoring system was built. Through data collection and feedback based on work distribution sheet, the backwards status coordination was implemented. At last, the validity of the proposed technique was verified by an application example.

scholarly journals A Wrist Sensor Sleep Posture Monitoring System: An Automatic Labeling Approach

2019 ◽  
Author(s):  
Po-Yuan Jeng ◽  
Li-Chun Wang ◽  
Chaur-Jong Hu ◽  
Dean Wu
Keyword(s):  
Home Care ◽  
Monitoring System ◽  
Monitoring Systems ◽  
Learning Approaches ◽  
Posture Monitoring ◽  
Labeling Approach ◽  
Percent Accuracy ◽  
Monitoring Service ◽  
User Friendly ◽  
Sleep Posture

Sleep postures monitoring systems in the hospital aim at transforming sensing signals into quantitative data to characterize the sleep behaviors of the patient. However, a home-care sleep posture monitoring system needs to be user friendly. In this paper, we present iSleePost - a user-friendly home-care intelligent sleep posture monitoring system. We address the labor-intensive labeling issue of traditional machine learning approaches in the training phase. Our proposed mobile health (mHealth) system leverages the communications and computation capabilities of mobile phones for provisioning a continuous sleep posture monitoring service. Our experiments show that iSleePost can achieve 90 percent accuracy in recognizing sleep postures. More importantly, iSleePost demonstrates that an easily-wear wrist sensor can accurately quantify sleep postures.

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