Evidence map›Paper›PMID 42465309›Full record

ArticlebioRxiv : the preprint server for biology2026

Device-embedded accelerometry complements neural signals for tracking parkinsonian motor states.

Tao Liu, Jiaang Yao, Bahman Abdi-Sargezeh, Abhinav Sharma, Camille Lasbareilles, Robert Tsi Lok Ho, Jackson T S Cheung, Timothy Denison, Huiling Tan, Wolf-Julian Neumann and 5 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Tao LiuMRC Centre of Research Excellence in Restorative Neural Dynamics, University of Oxford, Oxford, UK.ORCID 0000-0001-7098-4285
Jiaang YaoWeill Institute for Neurosciences, University of California San Francisco, San Francisco, USA.ORCID 0000-0001-7062-2508
Bahman Abdi-SargezehMRC Centre of Research Excellence in Restorative Neural Dynamics, University of Oxford, Oxford, UK.ORCID 0009-0003-8362-7350
Abhinav SharmaMRC Centre of Research Excellence in Restorative Neural Dynamics, University of Oxford, Oxford, UK.ORCID 0000-0002-9296-3386
Camille LasbareillesMRC Centre of Research Excellence in Restorative Neural Dynamics, University of Oxford, Oxford, UK.ORCID 0000-0001-7433-4597
Robert Tsi Lok HoDepartment of Neurosurgery, University of California San Francisco, San Francisco, USA.ORCID 0000-0002-1430-8861
Jackson T S CheungFaculty of Medical Sciences, University College London, London, UK.ORCID 0009-0004-4490-2505
Timothy DenisonMRC Centre of Research Excellence in Restorative Neural Dynamics, University of Oxford, Oxford, UK.ORCID 0000-0002-5404-4004
Huiling TanMRC Centre of Research Excellence in Restorative Neural Dynamics, University of Oxford, Oxford, UK.ORCID 0000-0001-8038-3029
Wolf-Julian NeumannWyss Center for Bio- and Neuroengineering, Geneva, Switzerland.ORCID 0000-0002-6758-9708
Minghan Max ZhuWeill Institute for Neurosciences, University of California San Francisco, San Francisco, USA.ORCID 0009-0004-9393-7157
Sebastian LiuDepartment of Neurosurgery, University of California San Francisco, San Francisco, USA.ORCID 0009-0007-8191-5251
Philip A StarrWeill Institute for Neurosciences, University of California San Francisco, San Francisco, USA.ORCID 0000-0003-2733-4003
Simon LittleWeill Institute for Neurosciences, University of California San Francisco, San Francisco, USA.ORCID 0000-0001-6249-6230
Ashwini OswalMRC Centre of Research Excellence in Restorative Neural Dynamics, University of Oxford, Oxford, UK.ORCID 0000-0002-0152-9294

Funding

Closed Loop Deep Brain Stimulation for Parkinson's DiseaseUH3NS100544 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI STARR, PHILIP ANDREW · 2016 to 2022
$4.1M
NINDS NIH HHS UH3 NS100544
6 · The paper itself

Abstract

Adaptive deep brain stimulation (aDBS) relies on physiological biomarkers to infer motor state and guide therapeutic stimulation in Parkinson's disease. However, neural biomarkers may themselves be altered by stimulation, potentially limiting their utility for closed-loop control. We address this limitation by testing whether DBS device-embedded accelerometers can accurately track Parkinsonian motor state across stimulation conditions. We analysed over 1,900 hours of chronic recordings of subthalamic nucleus (STN), sensorimotor cortical and device-embedded accelerometry signals acquired before and during continuous STN stimulation, alongside continuous wearable assessments of bradykinesia and dyskinesia. Across stimulation conditions, accelerometry-derived features robustly tracked motor symptom severity and outperformed neural features for symptom decoding. Mechanistically, total STN beta power - a widely used biomarker for aDBS - proved less informative because it conflates periodic and aperiodic neural processes with opposing relationships to motor state. Under active stimulation, periodic beta activity showed reduced coupling to symptom severity, whereas STN aperiodic activity, cortical periodic activity and cortico-subthalamic coherence remained comparatively stable. Together, these findings demonstrate that neural and behavioural biomarkers exhibit differential robustness during deep brain stimulation and identify device-embedded accelerometry as a robust behavioural biomarker of motor state, motivating its use in next-generation adaptive DBS systems.

Identifiers

PMID42465309
PMCPMC13370933

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.