Statistical measures of motor, sensory and cognitive performance across repeated robot-based testing

Journal of NeuroEngineering and Rehabilitation, Journal Year: 2020, Volume and Issue: 17(1)

Published: July 2, 2020

Abstract Background Traditional clinical assessments are used extensively in neurology; however, they can be coarse, which also make them insensitive to change. Kinarm is a robotic assessment system that has been for precise of individuals with neurological impairments. However, this precision leads the challenge identifying whether given change performance reflects significant an individual’s ability or simply natural variation. Our objective here derive confidence intervals and thresholds Standard Tests™ (KST). Methods We assessed participants twice within 15 days on all tasks presently available KST. determined 5–95% each task parameter, derived tested learning effects corrected false discovery rate (FDR) identify parameters effects. Finally, we calculated intraclass correlation type ICC (3,1) (ICC-C) quantify consistency across assessments. Results recruited average 56 per task. Confidence Z-Task Scores ranged between 0.84 1.41, threshold 1.19 2.00. 6/11 displayed were after FDR correction; these 4 primarily cognition cognitive-motor integration. ICC-C values from 0.29 0.70 Conclusions The present results provide statistical bounds individual KST as well changes repeated testing. Most measures had good inter-rater reliability. Tasks higher cognitive burden seemed more susceptible effects, should taken into account when interpreting longitudinal tasks.

Language: Английский

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Data Processing in Functional Near-Infrared Spectroscopy (fNIRS) Motor Control Research

Brain Sciences, Journal Year: 2021, Volume and Issue: 11(5), P. 606 - 606

Published: May 9, 2021

FNIRS pre-processing and processing methodologies are very important—how a researcher chooses to process their data can change the outcome of an experiment. The purpose this review is provide guide on fNIRS techniques pertinent field human motor control research. One hundred twenty-three articles were selected from examined basis methodologies. Information was gathered about most frequently used in field, which included frequency cutoff filters, wavelet smoothing general linear model (GLM). We discuss considerations for these techniques, as well those some alternative techniques. Additionally, discussed.

Language: Английский

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Acupuncture enhances brain function in patients with mild cognitive impairment: evidence from a functional-near infrared spectroscopy study

Neural Regeneration Research, Journal Year: 2021, Volume and Issue: 17(8), P. 1850 - 1850

Published: Dec. 10, 2021

Mild cognitive impairment (MCI) is a precursor to Alzheimer's disease. It imperative develop proper treatment for this neurological disease in the aging society. This observational study investigated effects of acupuncture therapy on MCI patients. Eleven healthy individuals and eleven patients were recruited study. Oxy- deoxy-hemoglobin signals prefrontal cortex during working-memory tasks monitored using functional near-infrared spectroscopy. Before treatment, experiments conducted control (HC) groups (MCI-0), followed by 24 sessions group. The initially carried out 6 weeks (two per week), after which performed again group (MCI-1). was another set that also lasted weeks, repeated (MCI-2). Statistical analyses classifications based activation maps as well temporal features performed. highest classification accuracies obtained binary connectivity 85.7% HC vs. MCI-0, 69.5% MCI-1, 61.69% MCI-2. mean from 5 seconds 28 maximum (i.e, max(5:28 seconds)) values 60.6% 56.9% 56.4% results reveal there change characteristics hemodynamic response due acupuncture. reflected reduction accuracy therapy, indicating patients' brain responses improved became comparable those subjects. A similar trend image feature. These indicate can be used

Language: Английский

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Experiment protocols for brain-body imaging of locomotion: A systematic review

Frontiers in Neuroscience, Journal Year: 2023, Volume and Issue: 17

Published: March 1, 2023

Human locomotion is affected by several factors, such as growth and aging, health conditions, physical activity levels for maintaining overall well-being. Notably, impaired a prevalent cause of disability, significantly impacting the quality life individuals. The uniqueness high prevalence human have led to surge research develop experimental protocols studying brain substrates, muscle responses, motion signatures associated with locomotion. However, from technical perspective, reproducing experiments has been challenging due lack standardized benchmarking tools, which impairs evaluation validation previous findings.This paper addresses challenges conducting systematic review existing neuroimaging studies on locomotion, focusing settings protocols, intensity, duration, distance, adopted imaging technologies, corresponding activation patterns. Also, this study provides practical recommendations future experiment protocols.The findings indicate that EEG preferred sensor detecting patterns, compared fMRI, fNIRS, PET. Walking most studied task, likely its fundamental nature status reference task. In contrast, running received little attention in research. Additionally, cycling an ergometer at speed 60 rpm using fNIRS provided some basis. Dual-task walking tasks are typically used observe changes cognitive function. Moreover, primarily focused healthy individuals, scenario closely resembling free-living real-world environments.Finally, outlines standards setting up based findings. It discusses impact neurological musculoskeletal well locomotive demands, design. also considers limitations imposed sensing techniques used, including acceptable level artifacts brain-body effects spatial temporal resolutions performance. various protocol constraints need be addressed analyzed explained.

Language: Английский

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Improving classification performance of four class FNIRS-BCI using Mel Frequency Cepstral Coefficients (MFCC)

Infrared Physics & Technology, Journal Year: 2020, Volume and Issue: 112, P. 103589 - 103589

Published: Nov. 30, 2020

Language: Английский

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