Identification and Characterization of Short-Term Motor Patterns in Rest Tremor of Individuals with Parkinson’s Disease

• Published in: Healthcare (Basel) Vol. 10; no. 12; p. 2536
• Main Authors: Rabelo, Amanda, Folador, João Paulo, Cabral, Ariana Moura, Lima, Viviane, Arantes, Ana Paula, Sande, Luciane, Vieira, Marcus Fraga, Almeida, Rodrigo Maximiano Antunes de, Andrade, Adriano de Oliveira
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 14.12.2022; MDPI
• Subjects: Complications and side effects; Diagnosis; Gyroscopes; Health aspects; Measurement; Methods; Muscle contraction; Neural oscillations; Neurology; Parkinson's disease; Physiology; Sensors; Tremor; Brazil; Switzerland; rest tremor; short-term motor patterns (STMPs); Parkinson’s disease; gyroscope
• ISSN: 2227-9032; 2227-9032
• DOI: 10.3390/healthcare10122536

(1) Background: The dynamics of hand tremors involve nonrandom and short-term motor patterns (STMPs). This study aimed to (i) identify STMPs in Parkinson’s disease (PD) and physiological resting tremor and (ii) characterize STMPs by amplitude, persistence, and regularity. (2) Methods: This study included healthy (N = 12, 60.1 ± 5.9 years old) and PD (N = 14, 65 ± 11.54 years old) participants. The signals were collected using a triaxial gyroscope on the dorsal side of the hand during a resting condition. Data were preprocessed and seven features were extracted from each 1 s window with 50% overlap. The STMPs were identified using the clustering technique k-means applied to the data in the two-dimensional space given by t-Distributed Stochastic Neighbor Embedding (t-SNE). The frequency, transition probability, and duration of the STMPs for each group were assessed. All STMP features were averaged across groups. (3) Results: Three STMPs were identified in tremor signals (p < 0.05). STMP 1 was prevalent in the healthy control (HC) subjects, STMP 2 in both groups, and STMP3 in PD. Only the coefficient of variation and complexity differed significantly between groups. (4) Conclusion: These results can help professionals characterize and evaluate tremor severity and treatment efficacy.