Early detection, empowered decisions.

ParkinSense is building a non-invasive, AI-driven digital platform to identify Parkinson's earlier and support clinicians with clear, data-backed insight.

Work with us Learn more

Latest News

ParkinSense team at Santander X UK Awards 2025

ParkinSense comes 2nd at the Santander X National Finals

Out of 800 applicants, ParkinSense secured 2nd place in the University Category at the Santander X UK Awards 2025.

ParkinSense pilot trials with Brunel University BORG group

ParkinSense completes successful pilot trials with Brunel Universities BORG group

During the week of December 8-12th, ParkinSense conducted pilot trials with Brunel University's BORG research group. We assessed our prototype application's usability, trust, and understanding, and conducted an experiment on trust in results, findings from which will be published soon.

Adam Lockhart Awarded Royal Academy of Engineering Enterprise Fellowship

Adam Lockhart, founder of ParkinSense, has been awarded a Royal Academy of Engineering Enterprise Fellowship to advance the development of a digital early-detection platform for Parkinson's Disease.

Evidence so far

100%

of Parkinson's cases correctly identified in initial proof-of-concept cohort (n=182, PD=80).

out of 6 initial false positives in our first evaluation have now been clinically diagnosed with Parkinson's Disease.

~1 year

Average time between ParkinSense detection and subsequent clinical diagnosis among confirmed cases.

£125,000

in competitive innovation funding secured to support clinical validation and product development.

Early internal results; ongoing validation with clinicians.

Features

Non-invasive by design

Software-only assessments make ParkinSense accessible to many more patients and healthcare systems.

Unique model architecture

Unique AI architecture to surface early risk and support diagnosis across varied PD presentations.

Easy for anyone, anywhere

A 25-minute guided assessment that can be done at home with a helper or in a clinical setting.

Clinician-centred

Clear risk scores, explanations, and red-flags co-designed with clinicians to fit real workflows.

Use Cases

Neurology triage

Prioritise referrals with structured summaries and risk scores to reduce waitlists.

Long-term risk monitoring

Track high-risk individuals and trigger early interventions as risk rises.

Decision support

Assist healthcare professionals in differentiating PD from similar neurological conditions more accurately.

Low-resource access

Provide highly specialised PD detection and support to low-resource settings.

Pharma recruitment

Identify suitable participants earlier to accelerate the quest for a Parkinson's cure.

Explore new applications

Have a specific use case in mind? We're open to discussing how ParkinSense can support your clinical or research needs.

We're always looking for collaborators.

Clinicians, researchers, engineers, healthcare providers, and partners — if you want to work with us, we'd love to talk.

Email us