Kinematic body sensor networks and behaviourmetrics for objective efficacy measurements in neurodegenerative disease drug trials

Abstract

We have deployed body sensor network (BSN) technology in clinical trials and developed behavioural analytics to quantify and monitor longitudinally the progression of Friedreich's Ataxia (FRDA) outside the lab. Patients and their carers administered themselves our ETHO1 wireless BSN and we captured motion time-series from patient sleep. We extracted behavioural biomarkers that objectively capture the progression of the disease throughout time and compares well with the SARA clinical scale gold-standard. Such clinical scales require patients to go through a series of lengthy tasks where clinicians observe patients' performance and aggregate a score that represents the stage of the disease. Unfortunately, such scales have been shown to be inconsistent across and within clinicians, as they are observation based subjective measures: Scales are highly dependent on the assessor's experience and they also have low sensitivity and resolution that fails to capture the slow disease progression in short periods of time, requiring longer clinical testing time frames. Using the neurobehavioural data we collected in our clinical trials, we extracted three behavioural biomarkers (MIM, SIM & KIM) based on patient movement intensity, activity and stillness while in bed. Our behavioural biomarkers correlation with the SARA clinical scale allows us to capture the disease progression in FRDA patients and establishes a proof of concept for BSN technology that we are applying towards more rapid efficacy measurements of drugs.