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Upper limb intention tremor assessment: opportunities and challenges in wearable technology.
Paredes-Acuna, Natalia; Utpadel-Fischler, Daniel; Ding, Keqin; Thakor, Nitish V; Cheng, Gordon.
Affiliation
  • Paredes-Acuna N; Institute for Cognitive Systems, Technical University of Munich, Arcisstraße 21, 80333, Munich, Germany. natalia.paredes@tum.de.
  • Utpadel-Fischler D; Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany.
  • Ding K; Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, USA.
  • Thakor NV; Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, USA.
  • Cheng G; Institute for Cognitive Systems, Technical University of Munich, Arcisstraße 21, 80333, Munich, Germany.
J Neuroeng Rehabil ; 21(1): 8, 2024 01 13.
Article in En | MEDLINE | ID: mdl-38218890
ABSTRACT

BACKGROUND:

Tremors are involuntary rhythmic movements commonly present in neurological diseases such as Parkinson's disease, essential tremor, and multiple sclerosis. Intention tremor is a subtype associated with lesions in the cerebellum and its connected pathways, and it is a common symptom in diseases associated with cerebellar pathology. While clinicians traditionally use tests to identify tremor type and severity, recent advancements in wearable technology have provided quantifiable ways to measure movement and tremor using motion capture systems, app-based tasks and tools, and physiology-based measurements. However, quantifying intention tremor remains challenging due to its changing nature. METHODOLOGY &

RESULTS:

This review examines the current state of upper limb tremor assessment technology and discusses potential directions to further develop new and existing algorithms and sensors to better quantify tremor, specifically intention tremor. A comprehensive search using PubMed and Scopus was performed using keywords related to technologies for tremor assessment. Afterward, screened results were filtered for relevance and eligibility and further classified into technology type. A total of 243 publications were selected for this review and classified according to their type body function level movement-based, activity level task and tool-based, and physiology-based. Furthermore, each publication's methods, purpose, and technology are summarized in the appendix table.

CONCLUSIONS:

Our survey suggests a need for more targeted tasks to evaluate intention tremors, including digitized tasks related to intentional movements, neurological and physiological measurements targeting the cerebellum and its pathways, and signal processing techniques that differentiate voluntary from involuntary movement in motion capture systems.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Tremor / Wearable Electronic Devices Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: J Neuroeng Rehabil Journal subject: ENGENHARIA BIOMEDICA / NEUROLOGIA / REABILITACAO Year: 2024 Document type: Article Affiliation country: Alemania Country of publication: Reino Unido

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Tremor / Wearable Electronic Devices Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: J Neuroeng Rehabil Journal subject: ENGENHARIA BIOMEDICA / NEUROLOGIA / REABILITACAO Year: 2024 Document type: Article Affiliation country: Alemania Country of publication: Reino Unido