Dystonia is a hyperkinetic movement disorder characterised by sustained or intermittent muscle contractions resulting in abnormal movements and postures (Albanese, A. et al. Phenomenology and classification of dystonia: A consensus update. Movement Disorders vol. 28 863–873 (2013) and up to 70% of individuals with dystonia report sleep difficulties (Bailey, G. A. et al. Sleep disturbance in movement disorders: Insights, treatments and challenges. J. Neurol. Neurosurg. Psychiatry 92, 723–736 (2021)).
Introduction
Gold standard sleep assessments require overnight admission to a sleep clinic with polysomnography – which can be expensive and time-consuming. Wearable devices, paired with a mobile application, provide the opportunity for a minimally intrusive monitoring system with minimal input from the patients.
Methodology
We recruited 50 individuals diagnosed with dystonia and 47 age- and sex-matched unaffected controls. Our primary objective was to identify sleep disturbances by comparing accelerometer-determined sleep variables between the cohorts.
Individuals wore a consumer-grade wrist device (Garmin vívosmart® 4) continuously over seven days on their non-dominant wrist, while completing patient-reported outcomes (PROs) using Aparito’s clinical trial platform.
Aparito utilised the Garmin health SDK to access the raw accelerometer data which is not otherwise available via Garmin Connect.
In this whitepaper we:
- Show the feasibility of using wearable devices in estimating sleep measures and architecture
- Emphasise the need for clinicians to screen for sleep disturbances as part of routine clinical assessments
- Identify that monitoring of sleep may be important for the prevention and management of non-motor symptoms
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