Wearables and the Internet of Things (IoT), applications, opportunities, and challenges: A Survey

FJ Dian, R Vahidnia, A Rahmati - IEEE access, 2020 - ieeexplore.ieee.org
Smart wearables collect and analyze data, and in some scenarios make a smart decision
and provide a response to the user and are finding more and more applications in our daily …

A systematic literature review of reviews on techniques for physical activity measurement in adults: a DEDIPAC study

KP Dowd, R Szeklicki, MA Minetto, MH Murphy… - International Journal of …, 2018 - Springer
The links between increased participation in Physical Activity (PA) and improvements in
health are well established. As this body of evidence has grown, so too has the search for …

[HTML][HTML] Physical human activity recognition using wearable sensors

F Attal, S Mohammed, M Dedabrishvili, F Chamroukhi… - Sensors, 2015 - mdpi.com
This paper presents a review of different classification techniques used to recognize human
activities from wearable inertial sensor data. Three inertial sensor units were used in this …

Activity recognition using cell phone accelerometers

JR Kwapisz, GM Weiss, SA Moore - ACM SigKDD Explorations …, 2011 - dl.acm.org
Mobile devices are becoming increasingly sophisticated and the latest generation of smart
cell phones now incorporates many diverse and powerful sensors. These sensors include …

A review of accelerometry-based wearable motion detectors for physical activity monitoring

CC Yang, YL Hsu - Sensors, 2010 - mdpi.com
Characteristics of physical activity are indicative of one's mobility level, latent chronic
diseases and aging process. Accelerometers have been widely accepted as useful and …

Optimal placement of accelerometers for the detection of everyday activities

I Cleland, B Kikhia, C Nugent, A Boytsov, J Hallberg… - Sensors, 2013 - mdpi.com
This article describes an investigation to determine the optimal placement of accelerometers
for the purpose of detecting a range of everyday activities. The paper investigates the effect …

[HTML][HTML] Machine learning methods for classifying human physical activity from on-body accelerometers

A Mannini, AM Sabatini - Sensors, 2010 - mdpi.com
The use of on-body wearable sensors is widespread in several academic and industrial
domains. Of great interest are their applications in ambulatory monitoring and pervasive …

Detection of physical activity types using triaxial accelerometers

J Skotte, M Korshøj, J Kristiansen… - … of physical activity …, 2014 - journals.humankinetics.com
Background: The aim of this study was to validate a triaxial accelerometer setup for
identifying everyday physical activity types (ie, sitting, standing, walking, walking stairs …

Preprocessing techniques for context recognition from accelerometer data

D Figo, PC Diniz, DR Ferreira, JMP Cardoso - Personal and Ubiquitous …, 2010 - Springer
The ubiquity of communication devices such as smartphones has led to the emergence of
context-aware services that are able to respond to specific user activities or contexts. These …

Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring

DM Karantonis, MR Narayanan… - IEEE transactions on …, 2006 - ieeexplore.ieee.org
The real-time monitoring of human movement can provide valuable information regarding
an individual's degree of functional ability and general level of activity. This paper presents …