The use of surface electromyography in muscle fatigue assessments–a review

The developments in physiological studies have established the importance of muscle fatigue estimation in various aspects including neurophysiological and medical research, rehabilitation, ergonomics, sports injuries and human-computer interaction. Surface electromyography signals are commonly used in muscle fatigue assessment. Techniques of surface EMG signal processing used to quantify muscle fatigue are not only based on time domain and frequency domain, but also on time–frequency domain. The developments of different signal analysis to extract different indices for muscle fatigue assessments are reviewed in this paper. Several indices in time, frequency, and time-frequency representations for muscle fatigue assessments have been identified. However the sensitivity of those indices needs to be investigated. Minimizing this issue becomes the objective of the recent research in muscle fatigue assessments

Character Recognition

Character recognition is one of the pattern recognition technologies that are most widely used in practical applications. This book presents recent advances that are relevant to character recognition, from technical topics such as image processing, feature extraction or classification, to new applications including human-computer interfaces. The goal of this book is to provide a reference source for academic research and for professionals working in the character recognition field

Dinamik kasılmalarda kas yorgunluğunun elektromiyogram ve mekanomiyogram ölçümleri ile analizi

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Kas yorgunluğunu tanımlayabilecek indeksleri arttırmak ve çeşitli parametrelerle ilişkisini belirlemek, kişilere özel antrenman programlarının geliştirilmesine, kişinin günlük hayattaki aktivite programını düzenlenmesine ve olası kas hasarlarının engellenmesine destek olacaktır. Bu doğrultuda yapılan çalışmada, Bruce protokolü ve 100m sprint performans testi ile gönüllülerin kaslarında oluşturulan yorgunluğun, farklı parametreler kullanılarak belirlenmesi hedef alınmıştır. Ayrıca çalışmaya katılan gönüllülerin antrene olup olmamasının, kas yorgunluğu tespiti üzerine etkileri de incelenmiştir. Literatürde yer alan yorgunluk tespit çalışmalarından farklı olarak bu çalışmada, sadece EMG, sadece MMG ve EMG-MMG kombinasyonları karşılaştırmalı olarak değerlendirilmiştir. Analizler için ilk olarak, spor geçmişi olan fakat şuan aktif bir spor dalıyla uğraşmayan kişilerden oluşan bir gönüllü grubu oluşturulmuştur. Çalışmanın başında antrene olmayan bu gönüllü grubunun belirlenen prosedüre göre kayıtları alınmıştır. Daha sonra aynı grup 8 hafta boyunca eğim antrenmanlarına katılmış ve kasları anterene hale geldiğinde, gönüllülere aynı prosedür tekrar uygulanmıştır. Elde edilen kayıtlar önişleme, DPD tabanlı enerji değerlerinin hesaplanması ve sınıflandırma aşamalarından geçirilmiştir. DPD ayrışımı 8 seviyede gerçekleştirilmiş ve sınıflandırma yapmak için ÇKYSA kullanılmıştır. Çalışma sonucunda EMG ve MMG kayıtlarının kombine uygulamasının, antrene olmayan kişilerin kas yorgunluğunu belirlemede daha başarılı bir yöntem olduğu tespit edilmiştir. Antrene kişilerin kas yorgunluğunun belirlenmesinde ise sadece EMG kayıtlarının kullanılması durumunda en başarılı sonuçlara ulaşılmıştır. Yine antrene kişilerde MMG'nin, EMG ile kombinasyona girmesi sonucunda bu yüksek test başarı değerlerini düşürdüğü görülmüştür. Ayrıca kas yorgunluğunun belirlenmesinde kullanılacak parametrelerin sadece kendi başına değerlendirilemeyeceği, EMG ve MMG kayıtlarının alındığı kişilerin antrenman düzeyinin, yaptığı aktivite ya da sporun EMG ve MMG'nin kas yorgunluğu belirlemedeki etkinliğini tamamen değiştirdiği açıkça ortaya konulmuştur.Increasing the indexes that can define muscle fatigue and determining it's relationship with various parameters will help the development of personel training programs, the regulation of personel daily life activity program and the prevention of possible muscle impairment. Therefore, in this study carried out, determination of the fatigue, which occurs in the volunteers' muscles via Bruce protocol and 100 m sprint performance test, was aimed by using various parameters. Moreover, the effects of whether the volunteers being trained or not, over the determination of muscle fatigue were analysed as well. Differently from the fatigue determination studies that are present in the literature, the records of solely Electromyogram (EMG), solely Mechanomyogram (MMG) and the combination of EMG and MMG were evaluated comperatively. For the analysis, firstly, a volunteers group, made of people who had a suport background in the past but now does not engage in any sport branches were performed. At the beginning of the study, the records of this group of volunteers who were untrained were taken according to the determined procedure. Afterwards, the same group participated in the trainings for 8 weeks and once their muscles became trained, the same procedure was applied to the volunteers again. The obtained records were passed through the stages of pre-processing, calculation of energy values based Wavelet Packet Transform (WPT), and classification. Decomposition of WPT was carried out in 8 levels and the Multi-layer Perceptron Artificial Neural Network (MLPNN) was used for classification. As the result of the study, it was determined that the combined application of EMG and MMG records was a more successful method for determining the muscle fatigue of those who were untrained. As for the determination of fatigue levels of those who were trained, the most successful results were attained by the use of solely EMG records. Once again, it was clearly revealed that the parameters to be used for the determination of muscle fatigue should not be evaluated single-handedly, and the training level of the persons, whose EMG and MMG records were taken, the daily activities they do and the sport activities they take part in totaly changed the effectiveness of determination of muscle fatigue by using EMG and MMG

Beyond the target area: an integrative view of tDCS-induced motor cortex modulation in patients and athletes

Transcranial Direct Current Stimulation (tDCS) is a non-invasive technique used to modulate neural tissue. Neuromodulation apparently improves cognitive functions in several neurologic diseases treatment and sports performance. In this study, we present a comprehensive, integrative review of tDCS for motor rehabilitation and motor learning in healthy individuals, athletes and multiple neurologic and neuropsychiatric conditions. We also report on neuromodulation mechanisms, main applications, current knowledge including areas such as language, embodied cognition, functional and social aspects, and future directions. We present the use and perspectives of new developments in tDCS technology, namely high-definition tDCS (HD-tDCS) which promises to overcome one of the main tDCS limitation (i.e., low focality) and its application for neurological disease, pain relief, and motor learning/rehabilitation. Finally, we provided information regarding the Transcutaneous Spinal Direct Current Stimulation (tsDCS) in clinical applications, Cerebellar tDCS (ctDCS) and its influence on motor learning, and TMS combined with electroencephalography (EEG) as a tool to evaluate tDCS effects on brain function161CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP465686/2014-1Não tem2014/50909-8; 13/10187–0; 14/10134–7The authors thank the Ministry of Education (MEC), FAPESP - São Paulo Research Foundation, Universidade Estadual de Londrina, Universidade Federal do Rio Grande do Norte and Universidade Federal do ABC for its support. Postdoctoral scholarships to DGSM from the Coordination for the Improvement of Higher Education Personnel (CAPES). Source(s) of financial support: This study was partially funded by grants to MB from NIH (NIH-NIMH 1R01MH111896, NIH-NINDS 1R01NS101362, NIH-NCI U54CA137788/U54CA132378, R03 NS054783) and New York State Department of Health (NYS DOH, DOH01-C31291GG), CEPID/BRAINN - The Brazilian Institute of Neuroscience and Neurotechnology (Process: 13/07559–3) to LML, Brazilian National Research Council (CNPq, Grant # 465686/2014-1) and the São Paulo Research Foundation (Grant # 2014/50909-8) to MSC, and Postdoctoral scholarships to AHO from FAPESP - Sao Paulo Research Foundation (Process: 13/10187–0 and 14/10134–7

Beyond the target area: an integrative view of tDCS-induced motor cortex modulation in patients and athletes

Transcranial Direct Current Stimulation (tDCS) is a non-invasive technique used to modulate neural tissue. Neuromodulation apparently improves cognitive functions in several neurologic diseases treatment and sports performance. In this study, we present a comprehensive, integrative review of tDCS for motor rehabilitation and motor learning in healthy individuals, athletes and multiple neurologic and neuropsychiatric conditions. We also report on neuromodulation mechanisms, main applications, current knowledge including areas such as language, embodied cognition, functional and social aspects, and future directions. We present the use and perspectives of new developments in tDCS technology, namely high-definition tDCS (HD-tDCS) which promises to overcome one of the main tDCS limitation (i.e., low focality) and its application for neurological disease, pain relief, and motor learning/rehabilitation. Finally, we provided information regarding the Transcutaneous Spinal Direct Current Stimulation (tsDCS) in clinical applications, Cerebellar tDCS (ctDCS) and its influence on motor learning, and TMS combined with electroencephalography (EEG) as a tool to evaluate tDCS effects on brain function

Effects of dance therapy on balance, gait and neuro-psychological performances in patients with Parkinson's disease and postural instability

Postural Instability (PI) is a core feature of Parkinson’s Disease (PD) and a major cause of falls and disabilities. Impairment of executive functions has been called as an aggravating factor on motor performances. Dance therapy has been shown effective for improving gait and has been suggested as an alternative rehabilitative method. To evaluate gait performance, spatial-temporal (S-T) gait parameters and cognitive performances in a cohort of patients with PD and PI modifications in balance after a cycle of dance therapy

Pseudo-online Detection and Classification for Upper-limb Movements from Scalp Electroencephalogram

Stroke has been a significant healthcare issue worldwide, leading to motor impairment and complicated rehabilitation procedures, which often last for years after lesion. In recent years, brain-computer interface (BCI) research shed some light on new approaches for motor ability recovery and potential neural plasticity inducement for stroke patients. Electroencephalogram (EEG) is widely used in BCI to measure brain activity. In this thesis study, nine healthy participants were recruited to perform four movements in a self-initiated manner, including left wrist extension (WE_L), right wrist extension (WE_R), left index finger extension (IE_L), and right index finger extension (IE_R). A hierarchical structure was proposed first to detect movement intentions from the rest state and then classify different movement types. Movement-related cortical potential (MRCP) and sensorimotor rhythm (SMR) were believed to associate with movement intention generation in human EEG. Thus, three frequency bands of EEG (0.05-5Hz, 5-40Hz, 0.05-40Hz) containing MRCP or SMR were investigated to provide features for detection and classification algorithms. In detection, a majority voting-based ensemble learning method was proposed to integrate the strongness of three algorithms, including support vector machine (SVM), EEGNET, and Riemannian feature-based SVM. The proposed method achieved an average true positive rate (TPR) of 79.6% ± 8.8%, false positives per minute (FPs/min) as 3.1 ± 1.2 within a latency of 91.4 ± 111.9ms. For classification, an adaptive boosting-based ensemble learning algorithm was proposed to classify movement pairs and four movements in pseudo-online and time-locked analyses. As a result, It proved the feasibility of classifying movements in different arms with higher than significant chance level accuracy. In summary, the proposed system offered a novel solution to decode upper-limb movements for rehabilitation-aimed BCI