An AutismAI Lab application
Research-grade movement analysis in the browser.
Volitiq turns any device with a camera into an objective motor assessment tool. Computer vision extracts skeletal pose from standard webcam video; the platform converts it into quantitative biomarkers that researchers, clinicians, and caregivers can act on. No installation, no specialist hardware, no clinic visit required.
Runs on any modern device with a camera. No installation, no plug-in, no specialist instrumentation. The webcam is the sensor.
Every clip produces a structured feature set: postural sway, head movement variability, gait spatiotemporal indices, bilateral asymmetry, smoothness metrics.
Autism-validated, with the same feature extractor generalising to fall risk, post-stroke recovery, and elderly mobility research.
The challenge
Motor differences are documented, but measuring them objectively is gated behind specialist clinics.
Motor differences appear in 34–80% of autistic individuals depending on the cohort and the measurement instrument used. They are clinically meaningful, they are reproducible across populations, and they are systematically under-measured because traditional motor assessment requires force transducers, motion capture systems, or other equipment confined to a small set of research clinics.
The same gating problem applies to aging research, post-stroke rehabilitation, and disability mobility studies. The biomarkers exist, the methods exist, but the apparatus does not travel. Volitiq removes the apparatus from the equation. The skeletal-pose features that drive modern motor research are recoverable from ordinary webcam video, with accuracy that already supports research use in many contexts.
What Volitiq measures
A structured feature set from every clip.
Centre-of-mass micro-oscillations recovered from standing pose, a documented digital phenotyping signal in ASD toddlers and a fall-risk indicator in older adults.
Frequency and amplitude of atypical head movement patterns, validated in ASD literature as an early behavioural marker (PMC6242931).
Joint-angle trajectories during everyday actions: reaching, grasping, manipulating objects, transferring between hands.
Step length, cadence, stride variability, double-support time, recovered from walking sequences in the camera frame.
Left-right discrepancies in coordinated movement, relevant to autism motor signatures and to post-stroke rehabilitation tracking.
Jerk-based and spectral-arc-length scores quantifying the qualitative smoothness of voluntary movement.
The feature library is extensible. Researchers needing a measurement that is not yet in the standard panel can request it through the collaboration channel; the underlying skeletal-pose stream supports many additional derivations.
Populations served
Autism is where we started. The pipeline generalises.
Motor differences are documented in 34–80% of autistic individuals. Volitiq operationalises the digital phenotyping literature into accessible measurements that any researcher or clinic with a webcam can collect.
Gait speed and gait variability are clinically validated biomarkers of fall risk, frailty, and early cognitive decline. The same skeletal-pose pipeline that scores autism motor signals produces these gait features directly.
Bilateral asymmetry and movement-smoothness scores are standard rehabilitation outcomes. Volitiq makes them measurable between clinic visits without specialist equipment, opening the door to higher-frequency outcome tracking.
The kinematic feature library is population-agnostic. Any condition with a measurable motor signature is a candidate population, provided the right normative reference can be assembled with research partners.
How a session works
From recording to research-ready features in minutes.
The participant performs a task (standing, walking, reaching, tool-use) in front of an ordinary webcam. Guided in-app instructions keep the framing consistent.
Skeletal landmarks are extracted frame by frame using validated computer vision models. The raw video can stay client-side when feasible.
The kinematic feature library converts the pose stream into quantitative biomarkers: sway, gait indices, asymmetry, smoothness.
Features land in research-ready formats with full provenance. Cohorts stay scoped to the partner research team that collected them.
Under the hood
Engineering choices that keep the barrier low.
What Volitiq does not claim
Three explicit non-claims.
Volitiq produces research-grade measurements. It is not a medical device and does not provide a diagnostic claim about any condition.
For sub-millimetre precision, marker-based motion capture remains the gold standard. Volitiq optimises for accessibility at research-useful accuracy, not laboratory ceiling accuracy.
Every score and trend exists to inform a human reader. Researchers interpret features. Clinicians decide on care. The platform surfaces signal cleanly; the interpretation is theirs.
Roadmap
Deeper kinematics, more populations, tighter integrations.
- →Hand and finger pose for fine-motor research.
- →Inter-segmental coordination metrics.
- →Improved low-light and occlusion robustness for in-home capture.
- →Normative references for older-adult and post-stroke populations.
- →Task templates for standard rehabilitation assessments.
- →Pilot partnerships in geriatric mobility research.
- →Cohort dashboards with group-level statistics and individual deviation scoring.
- →Direct R and Python notebook integrations for feature pulls.
- →Validated normative bands per task across age and cohort.
Try Volitiq, or bring it to your cohort.
Researchers can launch the app and capture a session in minutes. Labs and clinics interested in deploying Volitiq across a study cohort, or in proposing a new measurement, can reach the team through the collaboration page.