High-accuracy discrimination of Parkinson’s Disease participants from healthy controls using smartphones

S. Arora, M.A. Little, V. Venkataraman, S. Donohue, K. Biglan, E.R. Dorsey

Research output: Contribution to journalMeeting abstract

Abstract

Objective: To test the practicality and effectiveness of cheap, ubiquitous, consumer-grade smartphones to discriminate Parkinson’s disease (PD) subjects from healthy controls, using self-administered tests of gait and postural sway.
Background: Existing tests for the diagnosis of PD are based on subjective neurological examinations, performed in-clinic. Objective movement symptom severity data, collected using widely-accessible technologies such as smartphones, would enable the remote characterization of PD symptoms based on self-administered, behavioral tests. Smartphones, when backed up by interviews using web-based videoconferencing, could make it feasible for expert neurologists to perform diagnostic testing on large numbers of individuals at low cost. However, to date, the compliance rate of testing using smart-phones has not been assessed.
Methods: We conducted a one-month controlled study with twenty participants, comprising 10 PD subjects and 10 controls. All participants were provided identical LG Optimus S smartphones, capable of recording tri-axial acceleration. Using these smartphones, patients conducted self-administered, short (less than 5 minute) controlled gait and postural sway tests. We analyzed a wide range of summary measures of gait and postural sway from the accelerometry data. Using statistical machine learning techniques, we identified discriminating patterns in the summary measures in order to distinguish PD subjects from controls.
Results: Compliance was high all 20 participants performed an average of 3.1 tests per day for the duration of the study. Using this test data, we demonstrated cross-validated sensitivity of 98% and specificity of 98% in discriminating PD subjects from healthy controls.
Conclusions: Using consumer-grade smartphone accelerometers, it is possible to distinguish PD from healthy controls with high accuracy. Since these smartphones are inexpensive (around $30 each) and easily available, and the tests are highly non-invasive and objective, we envisage that this kind of smartphone-based testing could radically increase the reach and effectiveness of experts in diagnosing PD.
Original languageEnglish
Article numberPoster 30
Pages (from-to)e11
Number of pages1
JournalMovement Disorders
Volume28
Issue number10
Early online date13 Sep 2013
DOIs
Publication statusPublished - Sep 2013

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Parkinson Disease
Healthy Volunteers
Gait
Accelerometry
Videoconferencing
Smartphone
Neurologic Examination
Compliance
Interviews
Technology
Costs and Cost Analysis

Cite this

Arora, S., Little, M. A., Venkataraman, V., Donohue, S., Biglan, K., & Dorsey, E. R. (2013). High-accuracy discrimination of Parkinson’s Disease participants from healthy controls using smartphones. Movement Disorders, 28(10), e11. [Poster 30]. https://doi.org/10.1002/mds.25612
Arora, S. ; Little, M.A. ; Venkataraman, V. ; Donohue, S. ; Biglan, K. ; Dorsey, E.R. / High-accuracy discrimination of Parkinson’s Disease participants from healthy controls using smartphones. In: Movement Disorders. 2013 ; Vol. 28, No. 10. pp. e11.
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abstract = "Objective: To test the practicality and effectiveness of cheap, ubiquitous, consumer-grade smartphones to discriminate Parkinson’s disease (PD) subjects from healthy controls, using self-administered tests of gait and postural sway.Background: Existing tests for the diagnosis of PD are based on subjective neurological examinations, performed in-clinic. Objective movement symptom severity data, collected using widely-accessible technologies such as smartphones, would enable the remote characterization of PD symptoms based on self-administered, behavioral tests. Smartphones, when backed up by interviews using web-based videoconferencing, could make it feasible for expert neurologists to perform diagnostic testing on large numbers of individuals at low cost. However, to date, the compliance rate of testing using smart-phones has not been assessed.Methods: We conducted a one-month controlled study with twenty participants, comprising 10 PD subjects and 10 controls. All participants were provided identical LG Optimus S smartphones, capable of recording tri-axial acceleration. Using these smartphones, patients conducted self-administered, short (less than 5 minute) controlled gait and postural sway tests. We analyzed a wide range of summary measures of gait and postural sway from the accelerometry data. Using statistical machine learning techniques, we identified discriminating patterns in the summary measures in order to distinguish PD subjects from controls.Results: Compliance was high all 20 participants performed an average of 3.1 tests per day for the duration of the study. Using this test data, we demonstrated cross-validated sensitivity of 98{\%} and specificity of 98{\%} in discriminating PD subjects from healthy controls.Conclusions: Using consumer-grade smartphone accelerometers, it is possible to distinguish PD from healthy controls with high accuracy. Since these smartphones are inexpensive (around $30 each) and easily available, and the tests are highly non-invasive and objective, we envisage that this kind of smartphone-based testing could radically increase the reach and effectiveness of experts in diagnosing PD.",
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Arora, S, Little, MA, Venkataraman, V, Donohue, S, Biglan, K & Dorsey, ER 2013, 'High-accuracy discrimination of Parkinson’s Disease participants from healthy controls using smartphones', Movement Disorders, vol. 28, no. 10, Poster 30, pp. e11. https://doi.org/10.1002/mds.25612

High-accuracy discrimination of Parkinson’s Disease participants from healthy controls using smartphones. / Arora, S.; Little, M.A.; Venkataraman, V.; Donohue, S.; Biglan, K.; Dorsey, E.R.

In: Movement Disorders, Vol. 28, No. 10, Poster 30, 09.2013, p. e11.

Research output: Contribution to journalMeeting abstract

TY - JOUR

T1 - High-accuracy discrimination of Parkinson’s Disease participants from healthy controls using smartphones

AU - Arora, S.

AU - Little, M.A.

AU - Venkataraman, V.

AU - Donohue, S.

AU - Biglan, K.

AU - Dorsey, E.R.

PY - 2013/9

Y1 - 2013/9

N2 - Objective: To test the practicality and effectiveness of cheap, ubiquitous, consumer-grade smartphones to discriminate Parkinson’s disease (PD) subjects from healthy controls, using self-administered tests of gait and postural sway.Background: Existing tests for the diagnosis of PD are based on subjective neurological examinations, performed in-clinic. Objective movement symptom severity data, collected using widely-accessible technologies such as smartphones, would enable the remote characterization of PD symptoms based on self-administered, behavioral tests. Smartphones, when backed up by interviews using web-based videoconferencing, could make it feasible for expert neurologists to perform diagnostic testing on large numbers of individuals at low cost. However, to date, the compliance rate of testing using smart-phones has not been assessed.Methods: We conducted a one-month controlled study with twenty participants, comprising 10 PD subjects and 10 controls. All participants were provided identical LG Optimus S smartphones, capable of recording tri-axial acceleration. Using these smartphones, patients conducted self-administered, short (less than 5 minute) controlled gait and postural sway tests. We analyzed a wide range of summary measures of gait and postural sway from the accelerometry data. Using statistical machine learning techniques, we identified discriminating patterns in the summary measures in order to distinguish PD subjects from controls.Results: Compliance was high all 20 participants performed an average of 3.1 tests per day for the duration of the study. Using this test data, we demonstrated cross-validated sensitivity of 98% and specificity of 98% in discriminating PD subjects from healthy controls.Conclusions: Using consumer-grade smartphone accelerometers, it is possible to distinguish PD from healthy controls with high accuracy. Since these smartphones are inexpensive (around $30 each) and easily available, and the tests are highly non-invasive and objective, we envisage that this kind of smartphone-based testing could radically increase the reach and effectiveness of experts in diagnosing PD.

AB - Objective: To test the practicality and effectiveness of cheap, ubiquitous, consumer-grade smartphones to discriminate Parkinson’s disease (PD) subjects from healthy controls, using self-administered tests of gait and postural sway.Background: Existing tests for the diagnosis of PD are based on subjective neurological examinations, performed in-clinic. Objective movement symptom severity data, collected using widely-accessible technologies such as smartphones, would enable the remote characterization of PD symptoms based on self-administered, behavioral tests. Smartphones, when backed up by interviews using web-based videoconferencing, could make it feasible for expert neurologists to perform diagnostic testing on large numbers of individuals at low cost. However, to date, the compliance rate of testing using smart-phones has not been assessed.Methods: We conducted a one-month controlled study with twenty participants, comprising 10 PD subjects and 10 controls. All participants were provided identical LG Optimus S smartphones, capable of recording tri-axial acceleration. Using these smartphones, patients conducted self-administered, short (less than 5 minute) controlled gait and postural sway tests. We analyzed a wide range of summary measures of gait and postural sway from the accelerometry data. Using statistical machine learning techniques, we identified discriminating patterns in the summary measures in order to distinguish PD subjects from controls.Results: Compliance was high all 20 participants performed an average of 3.1 tests per day for the duration of the study. Using this test data, we demonstrated cross-validated sensitivity of 98% and specificity of 98% in discriminating PD subjects from healthy controls.Conclusions: Using consumer-grade smartphone accelerometers, it is possible to distinguish PD from healthy controls with high accuracy. Since these smartphones are inexpensive (around $30 each) and easily available, and the tests are highly non-invasive and objective, we envisage that this kind of smartphone-based testing could radically increase the reach and effectiveness of experts in diagnosing PD.

UR - http://onlinelibrary.wiley.com/doi/10.1002/mds.25612/abstract

U2 - 10.1002/mds.25612

DO - 10.1002/mds.25612

M3 - Meeting abstract

VL - 28

SP - e11

JO - Movement Disorders

JF - Movement Disorders

SN - 0885-3185

IS - 10

M1 - Poster 30

ER -