Parkinson’s in Real Life: What Wearables Are Teaching Us

Each year on April 11, World Parkinson’s Day invites us to reflect on how far the field has come since Dr. James Parkinson first described the “shaking palsy” in 1817. His work was grounded in careful observation. Patients were followed over time, allowing symptoms to be interpreted in context and meaning to emerge from their lived experience.

Fast forward to 2026. Our scientific tools are far more advanced. Yet in many ways, our measurement model still relies on snapshots. While Parkinson’s unfolds continuously, it is often captured in moments during the lifecycle of a clinical trial. This is now changing with the rise of wearable technology.

The Gold Standard for Assessment

Structured, clinician-administered rating scales have been standard in Parkinson’s clinical trials and have been used to quantify disease severity and progression. In particular, the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS‑UPDRS), remains the gold standard for assessing motor and non-motor symptoms and is foundational to regulatory decision making along with other clinical assessments. 

These assessments capture symptoms during a specific moment in time, as recorded in a diary or during scheduled clinic visits. However, motor and non-motor symptoms fluctuate across the day, vary with medication timing, sleep, stress, and activity, and may have meaningful changes between clinic visits. With some assessments limited to scheduled visits, what is measured may reflect conditions of the visit rather than the patient’s lived experience. What is lost between visits can matter as much as what is recorded during them. 

The Shift to Continuous Measurement

Limitations of clinic-based assessments are acknowledged within clinical research methodology. A smartwatch-based Parkinson’s protocol published in JMIR Research Protocols notes [RE1.1] that traditional neurological visits provide a narrow view of disease expression. The authors highlight that intermittent, in‑clinic assessments struggle to represent symptom fluctuations that occur over hours or days, particularly for motor features such as bradykinesia, tremor, and gait disturbance (JMIR Research Protocols, 2025).

This shift from episodic to continuous measurement is already operationalized in active clinical trials. In March 2026, reports confirmed that FDA‑cleared wearable platforms are being deployed in large, multi‑site Parkinson’s disease studies to complement standard clinic‑based assessments. In these trials, smartwatches are used to passively monitor motor symptoms during daily activities, offering longitudinal insight into symptom fluctuation and treatment response outside scheduled visits. Similar implementations have been described in sponsor communications emphasizing the role of wearable‑derived digital biomarkers alongside traditional endpoints.

It should be noted that these approaches are not positioned as replacement for clinician assessments. Instead, wearables are used to contextualize clinic findings, which helps to interpret what a particular MDS-UPDRS score represents across days or weeks of lived experience. 

Early Detection is Crucial

A 2025 study at Imperial College London reported that long‑term, passively collected smartwatch data can detect early Parkinson’s‑related brain changes more sensitively than established clinical risk scores. Using data from the Parkinson’s Progression Markers Initiative, participants wore smartwatches for an average of 16 months, capturing everyday measures such as movement, sleep, heart rate, and physical activity.

From this, the team developed a digital risk score that outperformed commonly used clinical criteria in identifying individuals with early dopamine dysfunction and misfolded α‑synuclein when compared against gold‑standard brain scans and cerebrospinal fluid tests. When combined with smell testing, the digital score identified over 80% of individuals with abnormal biological markers, suggesting that wearable‑based measures could offer a scalable, non‑invasive way to screen for Parkinson’s risk earlier and guide who should undergo more intensive diagnostic testing.

By establishing individual baselines and tracking deviations from expected patterns, passive digital biomarkers offer a framework for detecting longitudinal change that may not be visible during clinic visits.

Pattern-Based Understanding of Parkinson's

For Parkinson’s trials, this work supports a broader shift of moving from isolated measurements toward pattern‑based understanding of disease over time. Continuous digital biomarkers help contextualize clinical judgement, offering longitudinal insight into how symptoms and function evolve in daily life. From a trial design perspective, this strengthens the case for integrating wearable data alongside established endpoints to improve sensitivity to change while minimizing patient burden.

CROs can assist sponsors in the implementation of wearables in Parkinson’s and other clinical trials by considering and adding the following aspects:

•    Volume of data collected vs data analysis and interpretability
•    Standardization of devices and implementation across sites 
•    Alignment of continuous measures with regulatory expectations
•    Management of participant burden and compliance
•    Intergradation of endpoints of wearables with traditional clinical outcomes [RE2.1]

A question to ponder: what data are meaningful, and how should they be analyzed?

Volume of data collected vs data analysis and interpretability

Protocol-level discussions in wearable studies acknowledge this challenge as seen in a smartwatch-based Parkinson’s protocol published in JMIR Research Protocols. Here, Investigators highlight that extended monitoring must be paired with clearly defined analytic strategies to avoid overwhelming trials with signals that cannot be interpreted. Prespecified endpoints and thresholds for change are needed to avoid risking adding noise (rather than clarify) to high-frequency data. From a CRO perspective, interpretability can be ensured when the protocol and statistical analysis plan are in development. 

Standardization of Devices and Implementation Across Sites

Multi‑site trials introduce additional complexity. Differences in device versions, firmware updates, patient usage patterns, and site‑level workflows can all affect data consistency. Unlike traditional assessments that are administered uniformly during clinic visits, wearable data are generated continuously in uncontrolled environments.

Recent multinational Parkinson’s trials incorporating wearable platforms have demonstrated that scalability is feasible when supported by operational oversight and data harmonization. Sponsor‑announced implementations emphasize that wearable‑derived digital biomarkers are used alongside established assessments to maintain consistency across sites. For CROs, this reinforces the importance of centralized data governance and cross‑site alignment.  

Alignment of Continuous Measures with Regulatory Expectations

Regulatory acceptance remains a consideration with the transition into active Parkinson’s trials. While agencies have shown increasing openness to patient‑centered and digital measures, there are expectations for validity, reliability, and clinical relevance. Continuous digital endpoints must be clearly linked to meaningful clinical outcomes to support regulatory decision‑making, and documentation will need to be properly captured in the event of an inspection.

Patient‑centered research reinforces the importance of this alignment. A longitudinal study tracking individuals with early Parkinson’s disease showed that functional decline continued even when traditional symptom scores appeared stable. This shows the value of real‑world measurement in parallel with the challenge of interpreting change over time. Translating these insights into regulatory‑ready endpoints requires justification, which can be built into trial design. 

Management of Participant Burden and Compliance  

Wearable technologies carry strength in their low active burden: data are collected passively, reducing the need for frequent clinic visits or manual reporting. Although passive, there is still some burden associated with device adherence, usability, charging requirements, and data privacy concerns. These can all influence sustained participation. The JMIR Research Protocols study notes that long‑term compliance is essential for longitudinal data quality, particularly when trials depend on extended monitoring outside clinical settings. From a CRO standpoint, patient engagement strategies, clear instructions, staff and participant training, and responsive support systems become important to trial success. 

Intergradation of Endpoints of Wearables with Traditional Clinical Outcomes  

Finally, an important implication is integration. Wearable‑derived metrics are most powerful when interpreted alongside traditional clinical assessments. Continuous data can contextualize an MDS‑UPDRS score, help explain variability between visits, and reveal trends that episodic assessments alone may miss.

From a CRO perspective, it is evident that wearables represent a meaningful evolution in how Parkinson’s disease can be measured between clinic visits. At the same time, successful implementation depends on proper planning, operational oversight, and regulatory alignment.

References 

Author:
Alaina Dobos
Senior Clinical Trial Manager