Wearable device aims to help researchers track Parkinson’s
Clario-Oxford collaboration looks to advance clinical research
Clario and the University of Oxford are testing a wearable device to see how effective it is at tracking subtle changes in Parkinson’s disease, with the aim of improving clinical research.
Clario’s Opal wearable sensor device has demonstrated the ability to detect motor changes faster than traditional clinical evaluations. The current study, which has enrolled its first participant, will evaluate how effectively Opal can capture these changes outside the clinic and contribute to the development of validated digital movement endpoints — objective, quantifiable markers of motor performance that can be used in clinical trials to track disease progression and assess the impact of investigational therapies.
A team led by Chrystalina Antoniades, PhD, a professor at Oxford and head of the university’s Neurometrology Lab, will study the device’s use in remote settings, with patients performing prescribed tasks in home and researchers passively monitoring their activities.
“Our collaboration with Professor Antoniades and her team is an exciting step forward in Parkinson’s research,” Ellen Street, executive vice president and general manager for digital physiology at Clario, said in a company press release. “The team’s research combined with the unique capabilities of the Opal device can improve monitoring of disease progression and enable a greater ability to understand the effect of a drug candidate in Parkinson’s patients.”
Parkinson’s disease is characterized by hallmark motor symptoms that include tremors, stiffness, problems with balance and walking (gait), and abnormally slow movements. These symptoms gradually worsen as the disease progresses.
Detailed data help predict fall risk
Clinicians typically monitor changes in motor symptoms using standardized assessments that often are time-consuming and subjective. These tests are conducted in controlled settings, offering a limited snapshot of a patient’s daily motor performance. Subtle changes in movement may go unnoticed between visits, and variations in clinician judgment can affect how symptoms are rated, especially in cases where symptom progression may be less obvious.
The Opal device addresses this gap by using a series of lightweight, body-worn sensors — typically placed on the ankles, wrists, lower back, and chest — to record real-time, high-resolution data on gait, balance, and mobility. The device can detect subtle changes “with a level of precision that surpasses traditional assessment methods,” Clario said.
Researchers working with the Oxford Quantification in Parkinsonism project previously analyzed these detailed motion data alongside machine-learning tools to identify digital measures capable of detecting disease progression over much shorter time periods.
The wearable technology could detect changes in Parkinson’s motor symptoms more rapidly than standard tests, researchers found.
Recent data showed that a three-minute in-office movement assessment could predict fall risk — a major cause of disability and reduced quality of life in people with Parkinson’s — with 84%–92% accuracy up to two years in advance, and 78% accuracy up to five years in advance.
These predictive capabilities may change how Parkinson’s disease is managed and how treatments are evaluated in clinical research, according to Clario.
”Integrating validated, objective measures into drug development will enable precise evaluation and accelerate optimized treatments for patients.”
The new phase of the Clario–Oxford collaboration will test the usability and effectiveness of Opal-collected data in remote, real-world environments.
The data will be analyzed using the Mobilise-D Digital Mobility Outcomes framework, which provides standardized methods for interpreting gait and movement patterns captured by wearable sensors. By applying this framework, the team aims to ensure that Opal’s digital measures meet regulatory standards.
Insights from the work are expected to support the establishment of regulatory-ready digital endpoints for future clinical trials, giving researchers and pharmaceutical developers a more sensitive and objective way to assess how therapies affect patients over time.
“We are excited to partner with Clario to enhance Parkinson’s research using Opal’s advanced movement analysis,” Antoniades said. “This collaboration will refine predictive models for fall risk and disease progression, improving patient outcomes. There is a crucial need for regulatory-approved digital movement endpoints in clinical trials to assess Parkinson’s therapies accurately. Integrating validated, objective measures into drug development will enable precise evaluation and accelerate optimized treatments for patients.”
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