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

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

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.

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.

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).

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.