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Using smart socks to assess mobility and fall risk

Researchers check the accuracy and consistency of wearable-sock measurements for mobility assessment and possible prediction of falls in Parkinson’s.

Learning by observing or collecting information · Study reference: NCT07281755

Plain-language introduction written with AI from the registry; not independently checked by a clinician. Read the original details below ↓

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Start (reported actual date)
2025-08-08
Main measurements finished (planned)
2027-09
Study finished (planned)
2027-09

Planned dates can move. A study finishing does not tell us when a paper will be published.

No results summary has been confirmed in the registry records we imported. See connected papers below; we keep checking after recruitment ends.

Changes we have recorded
  • 2026-10-11 — recruiting

These are dates we observed a change, not necessarily the dates it happened.

Papers connected to this study

No connected paper has been found yet. The tracker checks the growing library for study identifiers and registry-linked publications.

Who can join?

Age 50 years and over · Does not accept healthy volunteers

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Read all the rules for taking part

Sex eligibility reported by registry: all

Inclusion Criteria: * Clinical diagnosis of Parkinson's by a movement disorder specialist according to UK brain bank criteria. * Hoehn \& Yahr stages I-III * Able to attend Northumbria University, Newcastle Upon Tyne for study visits * Able to walk and stand unassisted for a minimum of 2-minutes Exclusion Criteria: * History of neurological disorders other than PD (e.g., Huntington's disease, stroke, traumatic brain injury, multiple sclerosis, Alzheimer's disease etc.) * Montreal Cognitive Assessment (MoCA) score \< 21 * Injury to the lower extremities within the past 6-weeks.
Full study name & original research details

Official study title

Objective Mobility Assessment Using Wearable Technology for Clinical Application in Parkinson's Disease: From Validation to Fall Prediction

Original description

The main objective of this observational trial is to explore the validity and reliability of DANU smart socks when used for mobility assessments in people with Parkinson's. Using a series of laboratory gold standard equipment, this project aims to compare the metrics observed by DANU to the reference standards. No intervention is included. Specifically, this study will explore metrics relating to walking (gait) and balance of a Parkinson's cohort through a series of motor tasks. Moreover, this study seeks to investigate the clinical validity of DANU outcome metrics exploring relationships with clinical scales, fall history and prospective falls.

Further description from the registry

Background: Mobility impairments are common in Parkinson's disease (PD) and increase the risk of falling. Data derived from wearable inertial measurement units can provide useful information regarding gait in different situations and environments, which may help to identify those at risk of falling. However, rigorous testing is required to evaluate whether new devices are fit for purpose. DANU Smart Socks are a multi-modal system for movement analysis, containing 15 silicone based capacitive pressure sensors and an IMU pod, with tri-axal accelerometers, gyroscope and magnetometers, currently at use within a sporting context. Potential has been highlighted for clinical use in people with Parkinson's (PwP). This study aims to evaluate the validity, reliability and usability of the DANU Sport System in PwP for balance and gait assessment. The V3+ framework for determining fit-for-purpose biometric monitoring devices will be employed, evaluating verification, usability, analytical and clinical validation. Methods: Institutional ethics have been obtained (Project ID: 8543). Utilising a a repeated measures observational design, participants will be asked to attend two visits to Northumbria University, Newcastle Upon Tyne. Visit 1: Participants will complete a series of clinical and cognitive measures including the Movement Disorders Society's-Unified Parkinson's Disease Rating Scale, Montreal Cognitive Assessment, Freezing of Gait Questionnaire and Falls Efficacy Scale. Following this, concurrent data collection will occur throughout a battery of motor tasks to observe gait/balance metrics. Laboratory references employed include Axivity AX6, Vicon 3D Motion Capture, APDM Mobility Lab, GAITRite and AMTI Force Plates. Mobility assessments include a 2-Minute Walk Test, 3 walkway trials, a Timed Up and Go and a series of 2-Minute Balance tasks. Visit 2: Participants attend a second visit to repeat the mobility assessment previously detailed utilizing DANU Smart Socks and APDM Mobility Lab systems to explore test-retest reliability. Wearable device (DANU) validity and reliability will be examined using intra-class correlation coefficients and Bland-Altman plots to compare to laboratory reference standards. Moreover time series plots will be employed to evaluate the raw data agreement.

Conditions reported: Parkinson Disease(PD)

Registry records for this study

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Study type
Observational
Interventions
Not reported
Phases
Not reported
Sponsor
Northumbria University
Start date reported by registry
2025-08-08 (actual)

Registry updated: 2026-02-12 · Status last verified by the registry submitter: 2025-09

Registry records retrieved 2026-10-13 (UTC). Individual records may have older updates. Recruitment and eligibility must be confirmed with the study team.

Contact the research team

Public study contacts supplied to the registry. Ask whether recruitment is still open and what participation involves.

Gabriella R Gatti, BSc · 01912273343 · gabriella.gatti@northumbria.ac.uk

Rodrigo Vitorio, PhD · 01912273343 · rodrigo.vitorio@northumbria.ac.uk

Study locations

Site status can differ from overall study status. “Status not reported” means local availability needs confirmation. Remote participation and travel arrangements must be checked with the team.

Northumbria University

Newcastle upon Tyne, United Kingdom

Recruiting

Gabriella R Gatti, BSc · 01912273343 · gabriella.gatti@northumbria.ac.uk

Rodrigo Vitorio, PhD · 01912273343 · rodrigo.vitorio@northumbria.ac.uk

Gabriella R Gatti, Bsc

Rodrigo Vitorio, PhD

Rosie Morris, PhD

Alan Godfrey, PhD

Samuel Stuart, PhD

Facility not reported

United Kingdom

Status not reported

The original descriptions and participation rules come from the registry. Participation is voluntary and does not guarantee benefit.