Muscle Fatigue Assessment During Cycle Ergometer Exercise Using Principal Component Analysis of Electromyogram Power Spectra

2016 ◽  
Vol 32 (6) ◽  
pp. 593-598 ◽  
Author(s):  
Igor Ramathur Telles Jesus ◽  
Roger Gomes Tavares Mello ◽  
Jurandir Nadal
Keyword(s):  
Principal Component Analysis ◽  
Muscle Fatigue ◽  
Vastus Lateralis ◽  
Power Spectra ◽  
Principal Component ◽  
Component Analysis ◽  
Fatigue Analysis ◽  
Cycle Ergometer ◽  
Vastus Lateralis Muscle ◽  
Ergometer Exercise

During muscle fatigue analysis some standard indexes are calculated from the surface electromyogram (EMG) as root mean square value (RMS), mean (Fmean), and median power frequency (Fmedian). However, these parameters present limitations and principal component analysis (PCA) appears to be an adequate alternative. In this context, we propose two indexes based on PCA to enhance the quantitative muscle fatigue analysis during cyclical contractions. Signals of vastus lateralis muscle were collected during a maximal exercise test. Twenty-four subjects performed the test starting at 12.5 W power output with increments of 12.5 W⋅min–1, maintaining cadence of 50 rpm until voluntary exhaustion. The epochs of myoelectric activation were identified and used to estimate the power spectra. PCA was then applied to the power spectra of each subject. The standard (ST) and Euclidean (ED) distances were employed to estimate the alteration occurred due to fatigue. For comparison, the standard indexes were calculated. ST, ED, and RMS value were adequate for muscle fatigue analysis. Among these parameters, ST was more sensitive with higher effect size. Moreover, the Fmean and Fmedian were not sensitive to fatigue. The proposed method based on PCA of EMG in frequency domain allowed producing fatigue indexes suitable for cyclical contractions.

scholarly journals Effects of face mask use on exercise during the covid-19 pandemic: the principal component analysis (PCA)

2021 ◽  
Author(s):  
Paloma Priscila Porreca ◽  
Mayara Jeronymo Uébe Mansur ◽  
Victor Paes Dias Gonçalves ◽  
Bárbara Vieira Bolckau Miranda ◽  
Marlana Ribeiro Monteiro
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Face Mask ◽  
Component Analysis ◽  
Cycle Ergometer ◽  
World Health ◽  
Vastus Lateralis Muscle ◽  
Total Body Mass ◽  
Maximum Time ◽  
The Individual

The COVID-19 pandemic also raised questions about the practice of physical activity using a face mask and how this would affect breathing and performance. The aim of this study was to investigate the effects of using a tissue face mask recommended by the World Health Organization (WHO) on the variation of heart rate (HR), minute volume (VE), and muscle O 2 saturation (SO 2 m) parameters during performing the incremental load exercise and verifying the maximum time obtained at the end of the exercise. A 21-year-old male, 85 kg of total body mass and 1.68 m of height were selected. The individual performed an incremental load test to maximum exhaustion on the XT cycle ergometer (TRG Fitness ®️ ) in two moments: No mask -Control (C); Cloth Mask (CM). The individual was instructed to maintain a cadence of 61-65 rpm and every 2 minutes a load of 30.8 watts was added until maximum exhaustion. A ventilometer VO2 Pro (Cefise ®️ ) and a near infrared spectroscopy sensor (Moxy ®️ ) were used, placed in the vastus lateralis muscle of the right leg.Data were analyzed every 20% of the total time (20%, 40%, 60%, 80% and 100%) under conditions C and CM. The parameters of HR, VE and SO 2 m were monitored throughout the test and the data were statistically processed by a software (Origin Pro ®️ 3.226) using a multivariate analysis technique (Principal Component Analysis -PCA) to analyze interrelationships between the variables. In test condition C, an eigenvalue of 2.979 was observed with two variables (VE and SO 2 m) associated with greater variation (PC1). The maximum time obtained at the end of the test was 1535 seconds. In the CM condition, na eigenvalue of 2.881 was observed with two variables (HR and SO 2 m) associated with greater variation (PC1). The maximum time obtained at the end of the test was1330 seconds. It is concluded that the use of CM reduces VE variation, which may be associated with greater airflow resistance. The greatest variation observed in HR was due to the use of CM, impacting the delay in the appearance of the plateau. In addition, the use of a tissue mask recommended by the WHO reduces the maximum exercise time performed on the cycle ergometer in a healthy individual. These findings are useful for evaluating the effects of using CM in high-performance sports. Additional studies in the elderly and people with lung or heart disease are needed.

scholarly journals Differences in Simulated EMG Activities between a Non-Rotational Shot and an Ordinary Instep Kick Identified by Principal Component Analysis

Proceedings ◽  
2020 ◽  
Vol 49 (1) ◽  
pp. 154
Author(s):  
Tasuku Miyoshi ◽  
Yasuhisa Kamada ◽  
Yoshiyuki Kobayashi
Keyword(s):  
Principal Component Analysis ◽  
Vastus Lateralis ◽  
Gluteus Maximus ◽  
Principal Component ◽  
Rectus Femoris ◽  
Component Analysis ◽  
Vastus Intermedius ◽  
Longus Muscle ◽  
Instep Kick ◽  
Tensor Fasciae Latae

The aim of this study was to clarify the major differences in the electromyographic (EMG) activities in the hip joint required to achieve a non-rotational (NR) shot as compared with an instep kick from the spatiotemporal data. For this purpose, simulated EMG activities obtained from NR shots and instep kicks were analyzed using principal component analysis (PCA). The PCA was conducted using an input matrix constructed from the time-normalized average and the standard deviation of the EMG activities (101 data x (15 muscles; iliacus, gluteus maximus, rectus femoris, biceos femoris, vastus lateralis, vastus medialis, vastus intermedius, semimembranosus, semitendinosus, sartorius, tensor fasciae latae muscle, adductor magnus muscle, adductor longus muscle, gasctrocnemius, and tibialis anterior)). The PCA revealed that the 3rd, 4th and 8th principal component vectors (PCVs) of the 10 generated PCVs were related to achieving the NR shot (p < 0.05).

scholarly journals Wavelet Power Spectral Domain Functional Principal Component Analysis for Feature Extraction of Epileptic EEGs

Computation ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 78
Author(s):  
Shengkun Xie
Keyword(s):  
Principal Component Analysis ◽  
Feature Extraction ◽  
Power Spectra ◽  
Principal Component ◽  
Component Analysis ◽  
Functional Principal Component Analysis ◽  
Eeg Signals ◽  
Feature Extraction Method ◽  
Functional Principal Component ◽  
Low Dimensional

Feature extraction plays an important role in machine learning for signal processing, particularly for low-dimensional data visualization and predictive analytics. Data from real-world complex systems are often high-dimensional, multi-scale, and non-stationary. Extracting key features of this type of data is challenging. This work proposes a novel approach to analyze Epileptic EEG signals using both wavelet power spectra and functional principal component analysis. We focus on how the feature extraction method can help improve the separation of signals in a low-dimensional feature subspace. By transforming EEG signals into wavelet power spectra, the functionality of signals is significantly enhanced. Furthermore, the power spectra transformation makes functional principal component analysis suitable for extracting key signal features. Therefore, we refer to this approach as a double feature extraction method since both wavelet transform and functional PCA are feature extractors. To demonstrate the applicability of the proposed method, we have tested it using a set of publicly available epileptic EEGs and patient-specific, multi-channel EEG signals, for both ictal signals and pre-ictal signals. The obtained results demonstrate that combining wavelet power spectra and functional principal component analysis is promising for feature extraction of epileptic EEGs. Therefore, they can be useful in computer-based medical systems for epilepsy diagnosis and epileptic seizure detection problems.

Effect of prolonged exercise on muscle citrate concentration before and after endurance training in men

1993 ◽  
Vol 264 (2) ◽  
pp. E215-E220 ◽  
Author(s):  
A. R. Coggan ◽  
R. J. Spina ◽  
W. M. Kohrt ◽  
J. O. Holloszy
Keyword(s):  
Endurance Training ◽  
Citrate Synthase ◽  
Vastus Lateralis ◽  
Cycle Ergometer ◽  
Vastus Lateralis Muscle ◽  
Carbohydrate Utilization ◽  
Citrate Concentration ◽  
P Concentration ◽  
Ergometer Exercise ◽  
Before And After

It has been hypothesized that endurance training reduces carbohydrate utilization during exercise via citrate-mediated inhibition of phosphofructokinase (PFK). To test this hypothesis, vastus lateralis muscle biopsy samples were obtained from eight men before and immediately (approximately 10 s) after 2 h of cycle ergometer exercise at 60% of pretraining peak O2 uptake, both before and after 12 wk of endurance exercise training (3 days/wk running, 3 days/wk interval cycling). Training increased muscle citrate synthase (CS) activity from 3.69 +/- 0.48 (SE) to 5.30 +/- 0.42 mol.h-1.kg protein-1 and decreased the mean respiratory exchange ratio during exercise from 0.92 +/- 0.01 to 0.88 +/- 0.01 (both P < 0.001). Muscle citrate concentration at the end of exercise correlated significantly with CS activity (r = 0.70; P < 0.005) and was slightly but not significantly higher after training (0.80 +/- 0.19 vs. 0.54 +/- 0.19 mmol/kg dry wt; P = 0.16). Muscle glucose 6-phosphate (G-6-P) concentration at the end of exercise, however, was 31% lower in the trained state (1.17 +/- 0.10 vs. 1.66 +/- 0.27 mmol/kg dry wt; P < 0.05), in keeping with a 36% decrease in the amount of muscle glycogen utilized (133 +/- 22 vs. 209 +/- 19 mmol.kg dry wt-1.2 h-1; P < 0.01). The lower G-6-P concentration after training suggests that the training-induced reduction in carbohydrate utilization results from attenuation of flux before the PFK step in glycolysis and is not due to citrate-mediated inhibition of PFK.

scholarly journals Klasifikasi Sinyal Emg Pada Otot Tungkai Selama Berjalan Menggunakan Random Forest

2017 ◽  
Vol 1 (1) ◽  
pp. 51
Author(s):  
Darma Setiawan Putra ◽  
Adhi Dharma Wibawa ◽  
Mauridhi Hery Purnomo
Keyword(s):  
Principal Component Analysis ◽  
Feature Extraction ◽  
Random Forest ◽  
Gait Cycle ◽  
Cross Validation ◽  
Vastus Lateralis ◽  
Principal Component ◽  
Rectus Femoris ◽  
Component Analysis ◽  
Gastrocnemius Lateralis

Sinyal electromyography (EMG) merupakan suatu sinyal elektrik yang terdapat dalam lapisan otot selama gerakan aktif. Cara orang berjalan ditentukan oleh struktur otot dan tulang sehingga cara berjalan ini adalah unik dan dapat digunakan sebagai data biometrik. Pada penelitian ini, kami mengklasifikasi data EMG dari delapan jenis otot tungkai selama percobaan berjalan normal: Rectus Femoris, Vastus Lateralis, Vastus Medialis, Bicep Femoris, Semitendinosus, Gastrocnemius Lateralis, Gastrocnemius Medialis, dan Tibialis Anterior. Enam orang subyek diminta untuk berjalan di laboratorium GaitLab dengan 8 buah elektroda EMG ditempel pada otot mereka. Subyek diminta untuk berjalan sebanyak 1 gait cycle dengan 3 kali pengambilan data. Total dataset EMG untuk klasifikasi adalah sebanyak 18 buah. Metode graph feature extraction dan principal component analysis digunakan untuk ekstraksi fitur data EMG. Metode Random Forest digunakan untuk mengklasifikasi data EMG berdasarkan subyek. Metode pelatihan dan pengujian data EMG menggunakan cross validation (CV). Akurasi klasifikasi yang dihasilkan dengan menggunakan metode graph feature extraction adalah sebesar 88.88% dan metode principal component analysis adalah sebesar 72.22%. Hasil ini menunjukkan bahwa data EMG ketika berjalan dari 8 jenis otot tungkai dapat digunakan untuk identitas biometrik gaya berjalan (gait).

A German version of the Intermittent Claudication Questionnaire (ICQ): cultural adaptation and validation

VASA ◽  
2012 ◽  
Vol 41 (5) ◽  
pp. 333-342 ◽  
Author(s):  
Kirchberger ◽  
Finger ◽  
Müller-Bühl
Keyword(s):  
Principal Component Analysis ◽  
Intermittent Claudication ◽  
Completion Time ◽  
Short Form ◽  
Principal Component ◽  
Component Analysis ◽  
German Version ◽  
Average Completion Time ◽  
Sf 36 ◽  
Related Quality

Background: The Intermittent Claudication Questionnaire (ICQ) is a short questionnaire for the assessment of health-related quality of life (HRQOL) in patients with intermittent claudication (IC). The objective of this study was to translate the ICQ into German and to investigate the psychometric properties of the German ICQ version in patients with IC. Patients and methods: The original English version was translated using a forward-backward method. The resulting German version was reviewed by the author of the original version and an experienced clinician. Finally, it was tested for clarity with 5 German patients with IC. A sample of 81 patients were administered the German ICQ. The sample consisted of 58.0 % male patients with a median age of 71 years and a median IC duration of 36 months. Test of feasibility included completeness of questionnaires, completion time, and ratings of clarity, length and relevance. Reliability was assessed through a retest in 13 patients at 14 days, and analysis of Cronbach’s alpha for internal consistency. Construct validity was investigated using principal component analysis. Concurrent validity was assessed by correlating the ICQ scores with the Short Form 36 Health Survey (SF-36) as well as clinical measures. Results: The ICQ was completely filled in by 73 subjects (90.1 %) with an average completion time of 6.3 minutes. Cronbach’s alpha coefficient reached 0.75. Intra-class correlation for test-retest reliability was r = 0.88. Principal component analysis resulted in a 3 factor solution. The first factor explained 51.5 of the total variation and all items had loadings of at least 0.65 on it. The ICQ was significantly associated with the SF-36 and treadmill-walking distances whereas no association was found for resting ABPI. Conclusions: The German version of the ICQ demonstrated good feasibility, satisfactory reliability and good validity. Responsiveness should be investigated in further validation studies.

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