Smartphone-Based Assessment of Mobility and Manual Dexterity in Adult People with Spinal Muscular Atrophy.

Remote monitoring accelerometers drawing pinching turning typing walking wearable sensors

Journal

Journal of neuromuscular diseases
ISSN: 2214-3602
Titre abrégé: J Neuromuscul Dis
Pays: Netherlands
ID NLM: 101649948

Informations de publication

Date de publication:
03 Jul 2024
Historique:
medline: 12 7 2024
pubmed: 12 7 2024
entrez: 12 7 2024
Statut: aheadofprint

Résumé

More responsive, reliable, and clinically valid endpoints of disability are essential to reduce size, duration, and burden of clinical trials in adult persons with spinal muscular atrophy (aPwSMA). The aim is to investigate the feasibility of smartphone-based assessments in aPwSMA and provide evidence on the reliability and construct validity of sensor-derived measures (SDMs) of mobility and manual dexterity collected remotely in aPwSMA. Data were collected from 59 aPwSMA (23 walkers, 20 sitters and 16 non-sitters) and 30 age-matched healthy controls (HC). SDMs were extracted from five smartphone-based tests capturing mobility and manual dexterity, which were administered in-clinic and remotely in daily life for four weeks. Reliability (Intraclass Correlation Coefficients, ICC) and construct validity (ability to discriminate between HC and aPwSMA and correlations with Revised Upper Limb Module, RULM and Hammersmith Functional Scale - Expanded HFMSE) were quantified for all SDMs. The smartphone-based assessments proved feasible, with 92.1% average adherence in aPwSMA. The SDMs allowed to reliably assess both mobility and dexterity (ICC > 0.75 for 15/22 SDMs). Twenty-one out of 22 SDMs significantly discriminated between HC and aPwSMA. The highest correlations with the RULM were observed for SDMs from the manual dexterity tests in both non-sitters (Typing, ρ= 0.78) and sitters (Pinching, ρ= 0.75). In walkers, the highest correlation was between mobility tests and HFMSE (5 U-Turns, ρ= 0.79). This exploratory study provides preliminary evidence for the usability of smartphone-based assessments of mobility and manual dexterity in aPwSMA when deployed remotely in participants' daily life. Reliability and construct validity of SDMs remotely collected in real-life was demonstrated, which is a pre-requisite for their use in longitudinal trials. Additionally, three novel smartphone-based performance outcome assessments were successfully established for aPwSMA. Upon further validation of responsiveness to interventions, this technology holds potential to increase the efficiency of clinical trials in aPwSMA.

Sections du résumé

Background UNASSIGNED
More responsive, reliable, and clinically valid endpoints of disability are essential to reduce size, duration, and burden of clinical trials in adult persons with spinal muscular atrophy (aPwSMA).
Objective UNASSIGNED
The aim is to investigate the feasibility of smartphone-based assessments in aPwSMA and provide evidence on the reliability and construct validity of sensor-derived measures (SDMs) of mobility and manual dexterity collected remotely in aPwSMA.
Methods UNASSIGNED
Data were collected from 59 aPwSMA (23 walkers, 20 sitters and 16 non-sitters) and 30 age-matched healthy controls (HC). SDMs were extracted from five smartphone-based tests capturing mobility and manual dexterity, which were administered in-clinic and remotely in daily life for four weeks. Reliability (Intraclass Correlation Coefficients, ICC) and construct validity (ability to discriminate between HC and aPwSMA and correlations with Revised Upper Limb Module, RULM and Hammersmith Functional Scale - Expanded HFMSE) were quantified for all SDMs.
Results UNASSIGNED
The smartphone-based assessments proved feasible, with 92.1% average adherence in aPwSMA. The SDMs allowed to reliably assess both mobility and dexterity (ICC > 0.75 for 15/22 SDMs). Twenty-one out of 22 SDMs significantly discriminated between HC and aPwSMA. The highest correlations with the RULM were observed for SDMs from the manual dexterity tests in both non-sitters (Typing, ρ= 0.78) and sitters (Pinching, ρ= 0.75). In walkers, the highest correlation was between mobility tests and HFMSE (5 U-Turns, ρ= 0.79).
Conclusions UNASSIGNED
This exploratory study provides preliminary evidence for the usability of smartphone-based assessments of mobility and manual dexterity in aPwSMA when deployed remotely in participants' daily life. Reliability and construct validity of SDMs remotely collected in real-life was demonstrated, which is a pre-requisite for their use in longitudinal trials. Additionally, three novel smartphone-based performance outcome assessments were successfully established for aPwSMA. Upon further validation of responsiveness to interventions, this technology holds potential to increase the efficiency of clinical trials in aPwSMA.

Identifiants

pubmed: 38995798
pii: JND240004
doi: 10.3233/JND-240004
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Eduardo Arteaga-Bracho (E)

Biogen Digital Health, Biogen, Cambridge, MA, USA.

Gautier Cosne (G)

Biogen Digital Health, Biogen, Cambridge, MA, USA.

Christoph Kanzler (C)

Biogen Digital Health, Biogen, Cambridge, MA, USA.

Angelos Karatsidis (A)

Biogen Digital Health, Biogen, Cambridge, MA, USA.

Claudia Mazzà (C)

Biogen Digital Health, Biogen, Cambridge, MA, USA.

Joaquin Penalver-Andres (J)

Biogen Digital Health, Biogen, Cambridge, MA, USA.

Cong Zhu (C)

Biogen Digital Health, Biogen, Cambridge, MA, USA.

Changyu Shen (C)

Biogen Digital Health, Biogen, Cambridge, MA, USA.

Kelley Erb M (K)

Biogen Digital Health, Biogen, Cambridge, MA, USA.

Maren Freigang (M)

Department of Neurology, Dresden University Hospital, Dresden, Germany.

Hanna-Sophie Lapp (HS)

Department of Neurology, Dresden University Hospital, Dresden, Germany.

Simone Thiele (S)

Friedrich-Baur-Institute at the Department of Neurology, LMU University Hospital, LMU Munich.

Stephan Wenninger (S)

Friedrich-Baur-Institute at the Department of Neurology, LMU University Hospital, LMU Munich.

Erik Jung (E)

Department of Neurology, Heidelberg University Hospital, Heidelberg, Germany.

Susanne Petri (S)

Department of Neurology, Hannover Medical School, Hannover, Germany.

Markus Weiler (M)

Department of Neurology, Heidelberg University Hospital, Heidelberg, Germany.

Christoph Kleinschnitz (C)

Department of Neurology, Center for Translational Neuro- and Behavioral Sciences (C-TNBS), University Hospital Essen, Essen, Germany.

Maggie C Walter (MC)

Friedrich-Baur-Institute at the Department of Neurology, LMU University Hospital, LMU Munich.

René Günther (R)

Department of Neurology, Dresden University Hospital, Dresden, Germany.

Nolan Campbell (N)

Biogen Digital Health, Biogen, Cambridge, MA, USA.

Shibeshih Belachew (S)

Biogen Digital Health, Biogen, Cambridge, MA, USA.

Tim Hagenacker (T)

Department of Neurology, Center for Translational Neuro- and Behavioral Sciences (C-TNBS), University Hospital Essen, Essen, Germany.

Classifications MeSH