Title
Impact of sensor misplacement on estimating metabolic equivalent of task with wearables
Abstract
Metabolic equivalent of task (MET) indicates the intensity of physical activities. This measurement is used in providing physical activity intervention in many chronic illnesses such as coronary heart disease, type-2 diabetes, and cancer. Due to the small size, portability, low power consumption, and low cost, wearable motion sensors are widely used to estimate MET values. However, one major obstacle in widespread adoption of current wearable monitoring systems is that the sensors must be worn on predefined locations on the body. This imposes much discomfort for users as they are not allowed to wear the sensors on their own desired body locations. In addition, non-adherence to the predefined location of the sensors results in significant reduction in the accuracy of physical activity monitoring. In this paper, we propose a framework for sensor location-independent MET estimation. We introduce a sensor localization approach that allows users to wear the sensors on different body locations without having to adhere to a specific installation protocol. We study how such an algorithm impacts the performance of MET estimation algorithms. Using daily physical activity data, we demonstrate that an automatic sensor localization algorithm decreases the estimation error of the MET calculation by a factor of 2.3 compared to the case without sensor localization. Furthermore, our sensor localization algorithm achieves an accuracy of 90.8% in detecting on-body locations of wearable sensors. The integration of sensor localization and MET estimation achieves an accuracy of 80% in calculating the MET values of daily physical activities.
Year
DOI
Venue
2015
10.1109/BSN.2015.7299385
2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)
Keywords
Field
DocType
sensor misplacement effect,metabolic equivalent-of-task,MET estimation,physical activity intensity,chronic illness,coronary heart disease,type-2 diabetes,cancer,wearable motion sensor,wearable monitoring system,physical activity monitoring,body location,daily physical activity data,automatic sensor localization algorithm,wearable sensor localization
Obstacle,Monitoring system,Simulation,Computer science,Accelerometer,Wearable computer,Metabolic equivalent,Feature extraction,Software portability,Motion sensors,Embedded system
Conference
ISSN
Citations 
PageRank 
2376-8886
7
0.50
References 
Authors
15
5
Name
Order
Citations
PageRank
Parastoo Alinia11395.49
Ramyar Saeedi2818.00
Bobak Mortazavi3458.38
Ali Rokni470.50
Hassan Ghasemzadeh565661.36