Preliminary study on activity monitoring using an android smart‐watch

Abstract

The global trend for increasing life expectancy is resulting in aging populations in a number of countries. This brings to bear a pressure to provide effective care for the older population with increasing constraints on available resources. Providing care for and maintaining the independence of an older person in their own home is one way that this problem can be addressed. The EU Funded Unobtrusive Smart Environments for Independent Living (USEFIL) project is an assistive technology tool being developed to enhance independent living. As part of USEFIL, a wrist wearable unit (WWU) is being developed to monitor the physical activity (PA) of the user and integrate with the USEFIL system. The WWU is a novel application of an existing technology to the assisted living problem domain. It combines existing technologies and new algorithms to extract PA parameters for activity monitoring. The parameters that are extracted include: activity level, step count and worn state. The WWU, the algorithms that have been developed and a preliminary validation are presented. The results show that activity level can be successfully extracted, that worn state can be correctly identified and that step counts in walking data can be estimated within 3% error, using the controlled dataset.

Evaluation of a smartwatch-based intervention providing feedback of daily activity within a research-naive stroke ward: a pilot randomised controlled trial

“…The smartwatch specifications are shown in Additional file 1 . Data from the ZGPAX S8 tri-axial accelerometer is processed to extract a measure of overall body movement, the activity score, alongside an estimate of whether the watch was or was not worn [ 33 ]. Activity score has been shown to correlate highly ( p < .001) with energy expenditure obtained from whole room calorimetry [ 34 ].…”

Wearable sensors for gesture analysis in smart healthcare applications

“…In other research, Liu et al [48] fuse the information of an inertial sensor placed on the wrist with a Kinect camera to identify different gestures (agree, question mark, shake hand) to improve the interaction with a companion robot. Ahanathapillai et al [10] use an Android smartwatch to recognize common daily activities such as walking and ascending/descending stairs. The parameters that are extracted in this work include activity level and step count.…”

AART-BC: A sensor system for monitoring Assistive Technology use beyond the clinic

“…The wrist-wearable unit (WWU) is an Android 4 smartphone in a wristwatch form factor and uses a ZGPAX S8 as the base unit with a custom app written for it. The WWU has been developed and used in previous research [17], [18] and functions as a wearable data gathering and feedback platform. The WWU is capable of gathering accelerometer data from the patient's wrist and providing measures of physical activity, which correlate to calorific energy expenditure [19], as well as for example, whether or not a person is using a walking aid, such as a frame or stick.…”