Literature DB >> 31762829

Accelerometry data in health research: challenges and opportunities.

Marta Karas1, Jiawei Bai2, Marcin Strączkiewicz3, Jaroslaw Harezlak3, Nancy W Glynn4, Tamara Harris5, Vadim Zipunnikov2, Ciprian Crainiceanu2, Jacek K Urbanek6.   

Abstract

Wearable accelerometers provide detailed, objective, and continuous measurements of physical activity (PA). Recent advances in technology and the decreasing cost of wearable devices led to an explosion in the popularity of wearable technology in health research. An ever-increasing number of studies collect high-throughput, sub-second level raw acceleration data. In this paper, we discuss problems related to the collection and analysis of raw accelerometry data and refer to published solutions. In particular, we describe the size and complexity of the data, the within- and between-subject variability, and the effects of sensor location on the body. We also discuss challenges related to sampling frequency, device calibration, data labeling and multiple PA monitors synchronization. We illustrate these points using the Developmental Epidemiological Cohort Study (DECOS), which collected raw accelerometry data on individuals both in a controlled and the free-living environment.

Entities:  

Keywords:  Accelerometers; Accelerometry; Physical activity; Wearable accelerometers; Wearable computing

Year:  2019        PMID: 31762829      PMCID: PMC6874221          DOI: 10.1007/s12561-018-9227-2

Source DB:  PubMed          Journal:  Stat Biosci        ISSN: 1867-1764


  69 in total

1.  Normalization and extraction of interpretable metrics from raw accelerometry data.

Authors:  Jiawei Bai; Bing He; Haochang Shou; Vadim Zipunnikov; Thomas A Glass; Ciprian M Crainiceanu
Journal:  Biostatistics       Date:  2013-09-01       Impact factor: 5.899

2.  Quantification of physical activities by means of ambulatory accelerometry: a validation study.

Authors:  J B Bussmann; J H Tulen; E C van Herel; H J Stam
Journal:  Psychophysiology       Date:  1998-09       Impact factor: 4.016

3.  Imputation of missing data when measuring physical activity by accelerometry.

Authors:  Diane J Catellier; Peter J Hannan; David M Murray; Cheryl L Addy; Terry L Conway; Song Yang; Janet C Rice
Journal:  Med Sci Sports Exerc       Date:  2005-11       Impact factor: 5.411

4.  Validation of Gait Characteristics Extracted From Raw Accelerometry During Walking Against Measures of Physical Function, Mobility, Fatigability, and Fitness.

Authors:  Jacek K Urbanek; Vadim Zipunnikov; Tamara Harris; Ciprian Crainiceanu; Jaroslaw Harezlak; Nancy W Glynn
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2018-04-17       Impact factor: 6.053

5.  Estimating energy expenditure using body-worn accelerometers: a comparison of methods, sensors number and positioning.

Authors:  Marco Altini; Julien Penders; Ruud Vullers; Oliver Amft
Journal:  IEEE J Biomed Health Inform       Date:  2014-03-20       Impact factor: 5.772

Review 6.  Calibration and validation of wearable monitors.

Authors:  David R Bassett; Alex Rowlands; Stewart G Trost
Journal:  Med Sci Sports Exerc       Date:  2012-01       Impact factor: 5.411

7.  Automatic car driving detection using raw accelerometry data.

Authors:  M Strączkiewicz; J K Urbanek; W F Fadel; C M Crainiceanu; J Harezlak
Journal:  Physiol Meas       Date:  2016-09-21       Impact factor: 2.833

8.  Activity Recognition Invariant to Sensor Orientation with Wearable Motion Sensors.

Authors:  Aras Yurtman; Billur Barshan
Journal:  Sensors (Basel)       Date:  2017-08-09       Impact factor: 3.576

9.  Comparing accelerometer, pedometer and a questionnaire for measuring physical activity in bronchiectasis: a validity and feasibility study?

Authors:  B O'Neill; S M McDonough; J J Wilson; I Bradbury; K Hayes; A Kirk; L Kent; D Cosgrove; J M Bradley; M A Tully
Journal:  Respir Res       Date:  2017-01-14

10.  Optimal sensor placement for measuring physical activity with a 3D accelerometer.

Authors:  Simone T Boerema; Lex van Velsen; Leendert Schaake; Thijs M Tönis; Hermie J Hermens
Journal:  Sensors (Basel)       Date:  2014-02-18       Impact factor: 3.576

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  19 in total

1.  Adaptive empirical pattern transformation (ADEPT) with application to walking stride segmentation.

Authors:  Marta Karas; Marcin Stra Czkiewicz; William Fadel; Jaroslaw Harezlak; Ciprian M Crainiceanu; Jacek K Urbanek
Journal:  Biostatistics       Date:  2021-04-10       Impact factor: 5.899

2.  Development of a Novel Accelerometry-Based Performance Fatigability Measure for Older Adults.

Authors:  Yujia Susanna Qiao; Jaroslaw Harezlak; Kyle D Moored; Jacek K Urbanek; Robert M Boudreau; Pamela E Toto; Marquis Hawkins; Adam J Santanasto; Jennifer A Schrack; Eleanor M Simonsick; Nancy W Glynn
Journal:  Med Sci Sports Exerc       Date:  2022-06-24

3.  Scalar on time-by-distribution regression and its application for modelling associations between daily-living physical activity and cognitive functions in Alzheimer's Disease.

Authors:  Rahul Ghosal; Vijay R Varma; Dmitri Volfson; Jacek Urbanek; Jeffrey M Hausdorff; Amber Watts; Vadim Zipunnikov
Journal:  Sci Rep       Date:  2022-07-07       Impact factor: 4.996

4.  Physical Activity and Its Association with Traditional Outcome Measures in Pulmonary Arterial Hypertension.

Authors:  Jasleen Minhas; Haochang Shou; Steven Hershman; Roham Zamanian; Corey E Ventetuolo; Todd M Bull; Anna Hemnes; Murali M Chakinala; Stephen Mathai; Nadine Al-Naamani; Susan Ellenberg; Lea Ann Matura; Steven M Kawut; Anna Shcherbina
Journal:  Ann Am Thorac Soc       Date:  2022-04

Review 5.  Wearable Devices: Current Status and Opportunities in Pain Assessment and Management.

Authors:  Andrew Leroux; Rachael Rzasa-Lynn; Ciprian Crainiceanu; Tushar Sharma
Journal:  Digit Biomark       Date:  2021-04-19

Review 6.  Assessment of Physical Activity in Adults Using Wrist Accelerometers.

Authors:  Fangyu Liu; Amal A Wanigatunga; Jennifer A Schrack
Journal:  Epidemiol Rev       Date:  2022-01-14       Impact factor: 4.280

7.  An Optimal Self-Report Physical Activity Measure for Older Adults: Does Physical Function Matter?

Authors:  Nancy W Glynn; Alexa J Meinhardt; Kelsea R LaSorda; Jessica L Graves; Theresa Gmelin; Allison M Gerger; Paolo Caserotti; Robert M Boudreau
Journal:  J Aging Phys Act       Date:  2020-08-12       Impact factor: 2.109

8.  Augmented Movelet Method for Activity Classification Using Smartphone Gyroscope and Accelerometer Data.

Authors:  Emily J Huang; Jukka-Pekka Onnela
Journal:  Sensors (Basel)       Date:  2020-07-02       Impact factor: 3.576

9.  Objective Characterization of Activity, Sleep, and Circadian Rhythm Patterns Using a Wrist-Worn Actigraphy Sensor: Insights Into Posttraumatic Stress Disorder.

Authors:  Athanasios Tsanas; Elizabeth Woodward; Anke Ehlers
Journal:  JMIR Mhealth Uhealth       Date:  2020-04-20       Impact factor: 4.773

10.  Validity of Hip and Ankle Worn Actigraph Accelerometers for Measuring Steps as a Function of Gait Speed during Steady State Walking and Continuous Turning.

Authors:  Lucian Bezuidenhout; Charlotte Thurston; Maria Hagströmer; David Moulaee Conradsson
Journal:  Sensors (Basel)       Date:  2021-05-01       Impact factor: 3.576

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