Accuracy of the SWAY Mobile Cognitive Assessment Application

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Abstract

Background

Mobile electronic devices have become integral tools in addressing the need for portable assessment of cognitive function following neurocognitive/motor injury. SWAY Medical, Inc., has employed mobile device motion-based technology in the SWAY Cognitive Assessment (SWAY CA) application to assess cognitive function.

Purpose

The purpose of this study was to assess whether the SWAY CA application (reaction time, impulse control and inspective time) was able to reliably operate on different mobile devices and operating systems (iOS, Android). The study further sought to assess the validity of the SWAY CA application against the FDA approved ImPACT QT mobile device application.

Study Design

Original Research, observational study of validity.

Methods

88 healthy, young adults, 18 to 48 years ( mean= 22.09 ± sd=4.47 years) completed four, randomized and counter-balanced, reaction time tests (2- SWAY RT, 2- ImPACT QT) using different operating systems (iOS, Android) of 4 randomly assigned mobile devices.

Results

ANOVAs reported the SWAY CA application (reaction time, impulse control, inspection time) operated reliably with iPhone 6S, Samsung Galaxy S9, and iPad Pro 5 mobile devices ( p > 0.05), respectively. Google Pixel 3 reliability with SWAY CA application remains undetermined. SWAY CA simple reaction motion measures were in agreement ( r = -0.46 to 0.22, p ≤ 0.05) with several ImPACT QT reaction time measures. SWAY CA impulse control and inspection time measures are weakly correlated ( r = -0.25 to -0.46, p ≤ 0.05) with five ImPACT QT reaction time measures.

Conclusion

The motion-based SWAY CA mobile device application appears to reliably operate when being administered on different mobile devices and software operating systems. Furthermore, the SWAY CA application appears to be comparable to the ImPACT QT and serve as a valid tool for assessing reaction time measures.

Level of Evidence

Level 2b (observational study of validity).

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Most cited references 27

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Mobile devices and apps for health care professionals: uses and benefits.

C Lee Ventola (2014)

Health care professionals' use of mobile devices is transforming clinical practice. Numerous medical software applications can now help with tasks ranging from information and time management to clinical decision-making at the point of care.

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Factors influencing the latency of simple reaction time

David Woods, John M. Wyma, E. Yund … (2015)

Simple reaction time (SRT), the minimal time needed to respond to a stimulus, is a basic measure of processing speed. SRTs were first measured by Francis Galton in the 19th century, who reported visual SRT latencies below 190 ms in young subjects. However, recent large-scale studies have reported substantially increased SRT latencies that differ markedly in different laboratories, in part due to timing delays introduced by the computer hardware and software used for SRT measurement. We developed a calibrated and temporally precise SRT test to analyze the factors that influence SRT latencies in a paradigm where visual stimuli were presented to the left or right hemifield at varying stimulus onset asynchronies (SOAs). Experiment 1 examined a community sample of 1469 subjects ranging in age from 18 to 65. Mean SRT latencies were short (231, 213 ms when corrected for hardware delays) and increased significantly with age (0.55 ms/year), but were unaffected by sex or education. As in previous studies, SRTs were prolonged at shorter SOAs and were slightly faster for stimuli presented in the visual field contralateral to the responding hand. Stimulus detection time (SDT) was estimated by subtracting movement initiation time, measured in a speeded finger tapping test, from SRTs. SDT latencies averaged 131 ms and were unaffected by age. Experiment 2 tested 189 subjects ranging in age from 18 to 82 years in a different laboratory using a larger range of SOAs. Both SRTs and SDTs were slightly prolonged (by 7 ms). SRT latencies increased with age while SDT latencies remained stable. Precise computer-based measurements of SRT latencies show that processing speed is as fast in contemporary populations as in the Victorian era, and that age-related increases in SRT latencies are due primarily to slowed motor output.

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Tracking the Evolution of Smartphone Sensing for Monitoring Human Movement

Michael B Del Rosario, Stephen J. Redmond, Nigel Lovell (2015)

Advances in mobile technology have led to the emergence of the “smartphone”, a new class of device with more advanced connectivity features that have quickly made it a constant presence in our lives. Smartphones are equipped with comparatively advanced computing capabilities, a global positioning system (GPS) receivers, and sensing capabilities (i.e., an inertial measurement unit (IMU) and more recently magnetometer and barometer) which can be found in wearable ambulatory monitors (WAMs). As a result, algorithms initially developed for WAMs that “count” steps (i.e., pedometers); gauge physical activity levels; indirectly estimate energy expenditure and monitor human movement can be utilised on the smartphone. These algorithms may enable clinicians to “close the loop” by prescribing timely interventions to improve or maintain wellbeing in populations who are at risk of falling or suffer from a chronic disease whose progression is linked to a reduction in movement and mobility. The ubiquitous nature of smartphone technology makes it the ideal platform from which human movement can be remotely monitored without the expense of purchasing, and inconvenience of using, a dedicated WAM. In this paper, an overview of the sensors that can be found in the smartphone are presented, followed by a summary of the developments in this field with an emphasis on the evolution of algorithms used to classify human movement. The limitations identified in the literature will be discussed, as well as suggestions about future research directions.

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Author and article information

Journal

Journal ID (nlm-ta): Int J Sports Phys Ther

Journal ID (iso-abbrev): Int J Sports Phys Ther

Journal ID (publisher-id): 2159

Title: International Journal of Sports Physical Therapy

Publisher: NASMI

ISSN (Electronic): 2159-2896

Publication date (Electronic, pub): 1 August 2021

Publication date (Electronic, collection): 2021

Volume: 16

Issue: 4

Pages: 991-1000

Affiliations

[1 ] Wichita State University

[2 ] Engineering and Ergonomics of Physical Activity, University Savoie Mont-Blanc; Sporttesting

[3 ] Independent Consultant

Author notes

Corresponding author: Heidi Ann VanRavenhorst-Bell, PhD Assistant Professor, Department of Human Performance Studies Wichita State University 1845 Fairmount St., Campus Box 016, Wichita, Kansas 67260-0016 Phone: 316.978.5150 Fax: 316.978.5451 E-mail: heidi.bell@wichita.edu

Article

Publisher ID: 24924

DOI: 10.26603/001c.24924

PMC ID: 8329324

PubMed ID: 34386278

SO-VID: 66c6e424-7c42-42e3-bed1-5d051f079f56

License:

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (4.0) which permits non-commercial use and sharing in any medium or format, provided the original author and source are credited. If you remix, transform, or build upon this work, you may not distribute the modified material.

Accuracy of the SWAY Mobile Cognitive Assessment Application

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Abstract

Background

Purpose

Study Design

Methods

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Conclusion

Level of Evidence

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Scientific Phone Apps and Mobile Devices

Most cited references 27

Mobile devices and apps for health care professionals: uses and benefits.

Factors influencing the latency of simple reaction time

Tracking the Evolution of Smartphone Sensing for Monitoring Human Movement

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