Identifying and Quantifying Neurological Disability via Smartphone

Embedded sensors of the smartphones offer opportunities for granular, patient-autonomous measurements of neurological dysfunctions for disease identification, management, and for drug development. We hypothesized that aggregating data from two simple smartphone tests of fine finger movements with di...

Full description

Bibliographic Details
Main Authors: Alexandra K. Boukhvalova, Emily Kowalczyk, Thomas Harris, Peter Kosa, Alison Wichman, Mary A. Sandford, Atif Memon, Bibiana Bielekova
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-09-01
Series:Frontiers in Neurology
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fneur.2018.00740/full
id doaj-d9d75f77dc58480a92048f2e7b90da82
record_format Article
spelling doaj-d9d75f77dc58480a92048f2e7b90da822020-11-25T00:42:25ZengFrontiers Media S.A.Frontiers in Neurology1664-22952018-09-01910.3389/fneur.2018.00740400883Identifying and Quantifying Neurological Disability via SmartphoneAlexandra K. Boukhvalova0Emily Kowalczyk1Emily Kowalczyk2Thomas Harris3Peter Kosa4Alison Wichman5Mary A. Sandford6Atif Memon7Bibiana Bielekova8Laboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, United StatesLaboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, United StatesDepartment of Computer Science, University of Maryland, College Park, MD, United StatesLaboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, United StatesLaboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, United StatesLaboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, United StatesLaboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, United StatesDepartment of Computer Science, University of Maryland, College Park, MD, United StatesLaboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, United StatesEmbedded sensors of the smartphones offer opportunities for granular, patient-autonomous measurements of neurological dysfunctions for disease identification, management, and for drug development. We hypothesized that aggregating data from two simple smartphone tests of fine finger movements with differing contribution of specific neurological domains (i.e., strength & cerebellar functions, vision, and reaction time) will allow establishment of secondary outcomes that reflect domain-specific deficit. This hypothesis was tested by assessing correlations of smartphone-derived outcomes with relevant parts of neurological examination in multiple sclerosis (MS) patients. We developed MS test suite on Android platform, consisting of several simple functional tests. This paper compares cross-sectional and longitudinal performance of Finger tapping and Balloon popping tests by 76 MS patients and 19 healthy volunteers (HV). The primary outcomes of smartphone tests, the average number of taps (per two 10-s intervals) and the average number of pops (per two 26-s intervals) differentiated MS from HV with similar power to traditional, investigator-administered test of fine finger movements, 9-hole peg test (9HPT). Additionally, the secondary outcomes identified patients with predominant cerebellar dysfunction, motor fatigue and poor eye-hand coordination and/or reaction time, as evidenced by significant correlations between these derived outcomes and relevant parts of neurological examination. The intra-individual variance in longitudinal sampling was low. In the time necessary for performing 9HPT, smartphone tests provide much richer and reliable measurements of several distinct neurological functions. These data suggest that combing more creatively-construed smartphone apps may one day recreate the entire neurological examination.https://www.frontiersin.org/article/10.3389/fneur.2018.00740/fullsmartphone appdiagnosticsmedical technologyprecision medicinemultiple sclerosisneurology
collection DOAJ
language English
format Article
sources DOAJ
author Alexandra K. Boukhvalova
Emily Kowalczyk
Emily Kowalczyk
Thomas Harris
Peter Kosa
Alison Wichman
Mary A. Sandford
Atif Memon
Bibiana Bielekova
spellingShingle Alexandra K. Boukhvalova
Emily Kowalczyk
Emily Kowalczyk
Thomas Harris
Peter Kosa
Alison Wichman
Mary A. Sandford
Atif Memon
Bibiana Bielekova
Identifying and Quantifying Neurological Disability via Smartphone
Frontiers in Neurology
smartphone app
diagnostics
medical technology
precision medicine
multiple sclerosis
neurology
author_facet Alexandra K. Boukhvalova
Emily Kowalczyk
Emily Kowalczyk
Thomas Harris
Peter Kosa
Alison Wichman
Mary A. Sandford
Atif Memon
Bibiana Bielekova
author_sort Alexandra K. Boukhvalova
title Identifying and Quantifying Neurological Disability via Smartphone
title_short Identifying and Quantifying Neurological Disability via Smartphone
title_full Identifying and Quantifying Neurological Disability via Smartphone
title_fullStr Identifying and Quantifying Neurological Disability via Smartphone
title_full_unstemmed Identifying and Quantifying Neurological Disability via Smartphone
title_sort identifying and quantifying neurological disability via smartphone
publisher Frontiers Media S.A.
series Frontiers in Neurology
issn 1664-2295
publishDate 2018-09-01
description Embedded sensors of the smartphones offer opportunities for granular, patient-autonomous measurements of neurological dysfunctions for disease identification, management, and for drug development. We hypothesized that aggregating data from two simple smartphone tests of fine finger movements with differing contribution of specific neurological domains (i.e., strength & cerebellar functions, vision, and reaction time) will allow establishment of secondary outcomes that reflect domain-specific deficit. This hypothesis was tested by assessing correlations of smartphone-derived outcomes with relevant parts of neurological examination in multiple sclerosis (MS) patients. We developed MS test suite on Android platform, consisting of several simple functional tests. This paper compares cross-sectional and longitudinal performance of Finger tapping and Balloon popping tests by 76 MS patients and 19 healthy volunteers (HV). The primary outcomes of smartphone tests, the average number of taps (per two 10-s intervals) and the average number of pops (per two 26-s intervals) differentiated MS from HV with similar power to traditional, investigator-administered test of fine finger movements, 9-hole peg test (9HPT). Additionally, the secondary outcomes identified patients with predominant cerebellar dysfunction, motor fatigue and poor eye-hand coordination and/or reaction time, as evidenced by significant correlations between these derived outcomes and relevant parts of neurological examination. The intra-individual variance in longitudinal sampling was low. In the time necessary for performing 9HPT, smartphone tests provide much richer and reliable measurements of several distinct neurological functions. These data suggest that combing more creatively-construed smartphone apps may one day recreate the entire neurological examination.
topic smartphone app
diagnostics
medical technology
precision medicine
multiple sclerosis
neurology
url https://www.frontiersin.org/article/10.3389/fneur.2018.00740/full
work_keys_str_mv AT alexandrakboukhvalova identifyingandquantifyingneurologicaldisabilityviasmartphone
AT emilykowalczyk identifyingandquantifyingneurologicaldisabilityviasmartphone
AT emilykowalczyk identifyingandquantifyingneurologicaldisabilityviasmartphone
AT thomasharris identifyingandquantifyingneurologicaldisabilityviasmartphone
AT peterkosa identifyingandquantifyingneurologicaldisabilityviasmartphone
AT alisonwichman identifyingandquantifyingneurologicaldisabilityviasmartphone
AT maryasandford identifyingandquantifyingneurologicaldisabilityviasmartphone
AT atifmemon identifyingandquantifyingneurologicaldisabilityviasmartphone
AT bibianabielekova identifyingandquantifyingneurologicaldisabilityviasmartphone
_version_ 1725282690449539072