Distinction between essential and physiological tremor using Hilbert-Huang transform

Ayache, Samar S.; Al-Ani, Tarik; Lefaucheur, J.-P.

doi:10.1016/j.neucli.2014.03.006

Cited by 10 publications

(4 citation statements)

References 27 publications

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“…The specific channel and brain region designs are shown in Table 2 and Figure 3 ( Valer et al, 2007 ; Morais et al, 2018 ; Lacerenza et al, 2021 ). Data from fNIRS were recorded, the signal-to-noise ratio was assessed using NIRStar acquisition software, and the raw data were processed using nirsLAB according to the modified Beer–Lambert law ( Slone et al, 2012 ; Ayache et al, 2014 ).…”

Section: Methodsmentioning

confidence: 99%

A single 1,500 m freestyle at maximal speed decreases cognitive function in athletes

Lai,

Huang,

Lin

et al. 2023

Front. Psychol.

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IntroductionPhysical exercise can improve cognitive function, and the degree of impact on cognitive function is related to exercise modality, intensity, and duration. However, few studies have been conducted on the effects of competitive sports on cognitive function. The 1,500 m freestyle is the longest pool-based swimming event in the Olympic Games. This study explores the effects of 1,500 m freestyle at maximal speed on athletes’ cognitive function and analyzes the potential mechanism of cognitive function reduction in freestyle at maximal speed from the perspective of hemoglobin oxygenation difference (Hbdiff).MethodsA total of 13 male university swimmers were required to take part in a 1,500 m freestyle competition, swimming at maximal speed. The relevant indicators, including cognitive function and freestyle at maximal speed, before and after the competition were tested and analyzed. Cognitive function was assessed using the Schulte grid test (SGT), the trail-making test (TMT), and the digit span test (DST). The neurobiological characteristics of cognitive function, such as the prefrontal cortex (PFC), response time (RT), and accuracy rate (ACC), were tested using functional near-infrared spectroscopy (fNIRS).ResultsA significant decrease in scores for SGT, TMT, and digit span test-backward (DST-B) (p < 0.01). Oxygenated hemoglobin (Oxy-Hb) concentrations in the right frontopolar area (R-FPA) of brain channels 8 (p < 0.01) and 9 (CH8, 9) (p < 0.05), the right dorsolateral prefrontal cortex (R-DLPFC) CH10 (p < 0.05), and the middle dorsolateral prefrontal cortex (M-DLPFC) CH18 (p < 0.01) were significantly altered, and the right area of the brain was activated. The total Oxy-Hb concentrations in the regions of interest (ROIs) of R-FPA, R-DLFPC, and M-DLFPC were changed significantly (p < 0.01).DiscussionThe exhaustive performance of a 1,500 m freestyle event resulted in both physical fatigue and a decline in cognitive function. This decline may be attributed to the activation of specific regions of interest, namely the FPA, DLPFC, and M-DLPFC, within the prefrontal cortex (PFC), as well as alterations in functional connectivity.

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Section: Methodsmentioning

confidence: 99%

A single 1,500 m freestyle at maximal speed decreases cognitive function in athletes

Lai,

Huang,

Lin

et al. 2023

Front. Psychol.

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“…EMG has been used to distinguish muscle activation depending on the neurological disease [ 70 – 72 ]; for example, Nisticò and Vescio et al [ 73 , 74 ] showed that during rest tremor, the activation of antagonist muscles is synchronous in subjects with ET and alternating in those with PD. EMG and accelerometer/IMU combinations [ 75 – 83 ] have been extensively used to discriminate PD, ET [ 84 – 89 ], physiological tremor (PH) [ 90 , 91 ], psychogenic tremor [ 92 , 93 ], advanced ET [ 94 ], and MS [ 95 ] from each other by using ML techniques on DWT and HT signal decomposition during, in its majority, stretch and steady positions. MMG [ 96 ] was recently used with EMG, force sensors, and IMUs to detect tremor differences in PD after deep brain stimulation [ 97 ].…”

Section: Technologies For Tremor Assessmentmentioning

confidence: 99%

“…The valuable research conducted by Morgan et al [ 115 ] and Deuschl et al [ 257 ], investigating intention tremor during activities that induce this type of tremor, can now be easily replicated using markerless pose estimation software, as done by Pang et al in PD [ 269 ]. On the other hand, IMU sensors have become practical and effective for tremor detection but require sensor fusion algorithms and signal processing techniques for reliable analysis [ 90 , 183 , 242 ]. Another study was performed by Carpinella et al [ 183 ] effectively employed the combined capabilities of EMD and HHT to accurately detect minute variations in intention tremor tasks.…”

Section: Conclusion: Future Avenues To Assess Intention Tremormentioning

confidence: 99%

Upper limb intention tremor assessment: opportunities and challenges in wearable technology

Paredes-Acuna,

Utpadel-Fischler,

Ding

et al. 2024

J NeuroEngineering Rehabil

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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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“…As alternatives, time-domain algorithms based on thresholds [10], parametric identification methods [11], STFT, and techniques based on empirical mode decomposition (EMD) [12] have been proposed in the literature.…”

Section: Introductionmentioning

confidence: 99%

Assessment of a hand tremor based on analysis of the accelerometer signal

Wilk

Olbrycht

2016

ELECTROTECHNICAL REVIEW

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This paper presents the method developed for the assessment of a tremor based on analysis of the output signals from a 3-axis accelerometer placed on the index finger of the right hand. Firstly, the signal representing only acceleration caused by involuntary movement of the hand is determined. The tremor frequency is obtained as the dominant frequency of the PSD estimated for short segments of this signal by using the AR model. The presented method allows us to evaluate variability of tremor frequency in typical neurological tests. Streszczenie. W artykule opisano metodę opracowaną do oceny drżenia na podstawie analizy sygnałów wyjściowych z trójosiowego akcelerometru, który został umieszczony na palcu wskazującym prawej ręki. Najpierw wyznaczany jest sygnał reprezentujący tylko przyśpieszenie wywołane mimowolnym ruchem ręki. Częstotliwość drżenia jest określana jako dominująca częstotliwość PSD estymowanej dla krótkich segmentów tego sygnału na podstawie modelu AR. Prezentowana metoda umożliwia ocenę zmienności częstotliwości drżenia w typowych testach neurologicznych. (Ocena drżenia ręki na podstawie analizy sygnału z akcelerometru).

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Distinction between essential and physiological tremor using Hilbert-Huang transform

Cited by 10 publications

References 27 publications

A single 1,500 m freestyle at maximal speed decreases cognitive function in athletes

A single 1,500 m freestyle at maximal speed decreases cognitive function in athletes

Upper limb intention tremor assessment: opportunities and challenges in wearable technology

Assessment of a hand tremor based on analysis of the accelerometer signal

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