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April 10, 2018; 90 (15 Supplement) April 22, 2018

Automatic Detection of ON/OFF states in Parkinson Disease Patients Using Wearable Sensor Technology (S3.007)

Vibha Anand, Erhan Bilal, Vesper Ramos, Melissa Naylor, Charmaine Demauele, Hao Zhang, Stephen Amato, Paul Wacnik, Farhan Hameed, Tairmae Kangarloo, Bryan Ho, Kelley Erb, Daniel Karlin
First published April 9, 2018,
Vibha Anand
1IBM T.J. Watson Research Center Cambridge MA United States
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Erhan Bilal
1IBM T.J. Watson Research Center Cambridge MA United States
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Vesper Ramos
2Pfizer Inc., Early Clinical Development, Worldwide Research and Development Cambridge MA United States
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Melissa Naylor
2Pfizer Inc., Early Clinical Development, Worldwide Research and Development Cambridge MA United States
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Charmaine Demauele
2Pfizer Inc., Early Clinical Development, Worldwide Research and Development Cambridge MA United States
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Hao Zhang
2Pfizer Inc., Early Clinical Development, Worldwide Research and Development Cambridge MA United States
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Stephen Amato
2Pfizer Inc., Early Clinical Development, Worldwide Research and Development Cambridge MA United States
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Paul Wacnik
2Pfizer Inc., Early Clinical Development, Worldwide Research and Development Cambridge MA United States
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Farhan Hameed
2Pfizer Inc., Early Clinical Development, Worldwide Research and Development Cambridge MA United States
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Tairmae Kangarloo
2Pfizer Inc., Early Clinical Development, Worldwide Research and Development Cambridge MA United States
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Bryan Ho
3Movement Disorders Program, Department of Neurology, Tufts Medical Center Boston MA United States
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Kelley Erb
2Pfizer Inc., Early Clinical Development, Worldwide Research and Development Cambridge MA United States
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Daniel Karlin
2Pfizer Inc., Early Clinical Development, Worldwide Research and Development Cambridge MA United States
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Citation
Automatic Detection of ON/OFF states in Parkinson Disease Patients Using Wearable Sensor Technology (S3.007)
Vibha Anand, Erhan Bilal, Vesper Ramos, Melissa Naylor, Charmaine Demauele, Hao Zhang, Stephen Amato, Paul Wacnik, Farhan Hameed, Tairmae Kangarloo, Bryan Ho, Kelley Erb, Daniel Karlin
Neurology Apr 2018, 90 (15 Supplement) S3.007;

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Abstract

Objective: To detect self-reported ON and OFF states in Parkinson Disease (PD) patients from wearable sensor technology.

Background: Reliably detecting ON/OFF states is important for monitoring PD treatment and progression. Currently, subjective patient diaries capture this information. We investigate if detection of motor signs of ON/OFF states can be achieved by using kinematic measurements from wearable sensor technology combined with a machine learning (ML) pipeline.

Design/Methods: Twenty-five PD subjects (19 males, 69±7 years) taking levodopa performed 10-meter Instrumented Stand and Walk (ISAW) tests in their ON and OFF states while wearing Ambulatory Parkinson Disease Monitoring (APDM) sensors on their sternum, wrists, lumbar and lower extremities. A neurologist scored each ISAW according to the MDS-UPDRS-III. We analyzed 98 kinematic features for significance to neurologist total motor score and ON/OFF using both statistical (repeated-measures ANOVA, step-wise mixed-model regression, likelihood-ratio test, ridge regression) and ML methods.

Results: Twenty-two features significantly differed between patient reported ON/OFF states, with the most significant being trunk transverse range-of-motion (RofM), arm RofM, mid-swing elevation, stride length, turn velocity, steps in turn and toe out angles. Estimates from regression model showed average difference of 14 points between OFF/ON states in total UPDRS score and 9 points when adjusted for 5 significant features for individual baseline (mean trunk transverse RofM, right arm RofM, and toe out angle having highest effect; coeff. −8.67, −5.25, −3.36 respectively). Several approaches were employed for predicting ON/OFF states based on these features: direct binary classification (acc=0.56), regression to total UPDRS score (acc=0.76), regression to PIGD sub-score (acc=0.64), and classification of ON-OFF/OFF-ON transitions using feature differences (Naïve Bayes: acc=0.74, AUC=0.78; Random Forest: acc=0.76, AUC=0.90).

Conclusions: Wearable sensor technology holds promise for detecting ON/OFF states in PD patients using an augmented ML approach. This could be particularly useful for monitoring response to therapy in an outpatient setting.

Disclosure: Dr. Anand has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with IBM. Dr. Bilal has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with IBM. Dr. Ramos has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Pfizer, Inc. Dr. Naylor has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Pfizer, Inc. Dr. Demauele has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Pfizer Inc., Biogen. Dr. Zhang has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Pfizer Inc. Dr. Amato has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Pfizer, Inc. Dr. Wacnik has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Pfizer, inc. Dr. Hameed has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Pfizer, Inc. Dr. Kangarloo has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Pfizer Inc. Dr. Ho has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Pfizer, Inc. Dr. Erb has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Pfizer, Inc. Dr. Karlin has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Pfizer Inc.

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