Digital endpoints & wearable monitoring for Parkinson’s and Movement Disorder Trials
Digital endpoints are objective, sensor-based measurements captured using wearable devices and apps, to track disease progression and treatment response in real-world settings.
How digital endpoints are transforming Parkinson's disease trials
Digital endpoints are transforming how Parkinson’s disease is measured in clinical research, with growing applications across other movement disorders. For sponsors and CROs running trials on Parkinson’s and other movement disorders, digital endpoints derived through wearable sensors provide objective, real-world data collection, and offer deeper insight into symptom progression, treatment response, and overall quality of life.
Digital endpoints for Parkinson’s clinical trials
Parkinson’s disease is defined by its cardinal motor symptoms: bradykinesia, tremor, rigidity, and postural instability, which are key biomarkers in clinical trials. Digital endpoints are increasingly used across trials on dopaminergic therapies (e.g. levodopa), disease-modifying treatments, and deep brain stimulation (DBS) and neuromodulation.
Why continuous wearable monitoring matters in movement disorders
Movement disorders are a group of nervous system conditions that affect movement. Parkinson’s disease is a progressive neurodegenerative disorder characterized by motor symptoms such as bradykinesia, tremor, rigidity, and postural instability, alongside non-motor complications that significantly impact quality of life. Parkinson’s symptoms fluctuate significantly throughout the day due to factors such as medication cycles, activity levels, and disease progression. Digital biomarkers and wearable devices, such as watches, apps, and other monitoring tools can address these challenges:
Capturing daily motor fluctuations
Detect “on/off” states and symptom variability throughout the day.
Objective measurement
Effectively supplement clinician-rated scales such as MDS-UPDRS.
Improved sensitivity to change
Identify subtle treatment effects that may not be visible during site visits.
Patient burden
Frequent site visits can be challenging, particularly for patients with mobility impairments. For trials, this can result in lower participation.
Key digital measures in Parkinson’s monitoring include:
It is possible to track real-time treatment response and symptoms in Parkinson’s patients while they are at home, using 30+ validated movement disorder algorithms, developed by PKG Health and provided by Empatica
- Bradykinesia
- Dyskinesia
- Sleep disturbances
- Wake After Sleep Onset (WASO)
- Tremor
- OFF time prediction
- Gait & Postural Stability
- Freezing of Gait
- Motor fluctuations
- Time spent immobile
Key digital endpoints in movement disorder clinical trials
It is possible to track real-time treatment response and symptoms in Parkinson’s patients while they are at home, using 30+ validated movement disorder algorithms, developed by PKG Health and provided by Empatica
What are the limitations of traditional Parkinson’s assessments?
Missing real-world context
Evaluations capture only brief snapshots of a patient’s status, without necessarily capturing how symptoms affect quality of life outside the clinic.
Intermittent data collection
Infrequent assessments miss symptom variability and transient events. This is key in Parkinson’s patients where variability appears on a daily basis.
Clinician and patient subjectivity
Ratings depend on clinician interpretation and patient self-reports, which provide valuable information but are affected by recall.
Patient burden
Frequent site visits can be challenging, particularly for patients with mobility impairments. For trials, this can result in lower participation.
Effectiveness of wearable devices in monitoring Parkinson’s Disease symptoms
Wearable devices equipped with accelerometers and gyroscopes used in Parkinson’s research have demonstrated strong potential in accurately and continuously monitoring key symptoms such as tremor, bradykinesia and dyskinesia.
- 95% sensitivity and 88% specificity comparing BKS with UPDRS III (Unified Parkinson's Disease Rating Scale).¹
- Highly significant correlation (R = 0.80, p < 0.0001) between DKS and AIMS (Abnormal Involuntary Movement Scale).¹
92.5% sensitivity and 92.9% specificity identifying tremor (PTT ≥ 0.8%).² - Wearable devices identify uncontrolled symptoms 72% of the time.³
Accelerometry data from wrist-worn sensors can measure step count in PD with <3% error rate.⁴
See publications
1. Griffiths RI, Kotschet K, Arfon S, et al. Automated assessment of bradykinesia and dyskinesia in Parkinson’s disease. J Parkinsons Dis. 2012;2(1):47-55.
2. Braybrook M, O’Connor S, Churchward P, et al. An Ambulatory Tremor Score for Parkinson’s Disease. J Parkinsons Dis. 2016;6(4):723-731.
3. Woodrow H, Horne M, Fernando C, Kotschet K, Treat to Target Study Group. A blinded, controlled trial of objective measurement in Parkinson’s disease. NPJ Parkinson’s Disease. 2020;6:35. https://doi.org/10.1038/s41531-020-00136-9
4. Shokouhi N, Khodakarami H, Fernando C, et al. Accuracy of Step Count Estimations in Parkinson’s Disease Can Be Predicted Using Ambulatory Monitoring. Front Aging Neurosci. 2022;14:904895. https://doi.org/10.3389/fnagi.2022.904895
Enabling scalable remote monitoring for Parkinson’s trials
Empatica provides a clinical-grade wearable platform designed to support continuous, remote monitoring in neurological clinical trials.
- FDA-cleared and CE-marked platform, devices and apps
- Continuous actigraphy and movement analysis for motor symptom tracking
- Continuous data collection for up to 14 days
- High patient adherence through comfortable, wrist-worn design
- 38 validated movement disorder measures
- Over 200 sleep and activity measures
- Secure data infrastructure supporting compliance requirements (GDPR, HIPAA)
Learn about our Clinical Trials offering
Additional resources
Advancing objective Parkinson’s monitoring in clinical practice: Evolving the PKG within the Empatica platform
WEBINAR
Beyond the clinic: Using continuous monitoring to better manage ‘OFF’ in Parkinson’s
WEBINAR
FDA Clears Empatica’s EmbraceMini for Sleep Monitoring
BLOG POST
Rethinking wearable compliance in trials: Evidence from real-world deployments
BLOG POST
Empatica Health Monitoring Platform for Parkinson's
Digital Info Pack
Frequently Asked Questions
What are relevant digital endpoints in Parkinson’s clinical trials?
Digital endpoints are objective, sensor-derived measurements such as tremor and gait speed, collected via wearable devices to assess disease progression and treatment response. Common digital endpoints in Parkinson’s clinical trials include bradykinesia scores (BKS), dyskinesia scores (DKS), tremor metrics (PTT), and sleep measures such as WASO. These endpoints can be used as primary, secondary, or exploratory outcomes depending on study design.
Are wearable devices validated for Parkinson’s research?
Yes, many wearable-derived measures have shown correlation with clinical scales and are increasingly used in clinical trials. Empatica’s EmbraceMini and EmbracePlus wearables have also shown near-100% equivalence with the PKG Watch when measuring Bradykinesia, Dyskinesia and Tremor. In addition, the Empatica Health Monitoring Platform is FDA-cleared and purpose-made for remote patient monitoring.
How are movement disorders traditionally measured in Parkinson’s trials?
They are traditionally assessed using clinical scales like MDS-UPDRS, but increasingly supplemented with continuous wearable-based measurements.
What are the benefits of continuous monitoring in Parkinson’s disease?
Continuous monitoring captures real-world symptom variability, improves sensitivity to change, and reduces reliance on subjective assessments.
Can digital biomarkers replace clinical scales?
Digital biomarkers are increasingly used as complementary endpoints to enhance trial sensitivity and patient-centricity.
How effective are wearable devices in monitoring Parkinson's symptoms?
Wearable devices have proven highly effective in monitoring Parkinson’s disease symptoms, particularly for capturing motor fluctuations and real-world patient experience. Equipped with sensors such as accelerometers and gyroscopes, wearable devices can continuously measure key motor symptoms including tremor, bradykinesia, dyskinesia, and gait impairment. These measurements provide objective, high-frequency data that supplements traditional clinical scales like MDS-UPDRS.