The effect of transcranial electrical stimulation on the relief of mental fatigue DOI Creative Commons
Ruijuan Chen, Lengjie Huang, Rui Wang

et al.

Frontiers in Neuroscience, Journal Year: 2024, Volume and Issue: 18

Published: June 17, 2024

Objective The presence of mental fatigue seriously affects daily life and working conditions. Non-invasive transcranial electrical stimulation has become an increasingly popular tool for relieving fatigue. We investigated whether direct current (tDCS) alternating (tACS) could be used to alleviate the state in a population healthy young adults compared their effects. Methods recruited 10 participants blank control, repeated measures study. Each participant received 15 min anodal tDCS, α-tACS, stimulation. Participants were required fill scale, perform test task collect ECG signals baseline, post-stimulus states. then assessed participants’ subjective scale scores, accuracy HRV characteristics separately. Results found that both tDCS α-tACS significantly ( P < 0.05) reduced improved on group, extent change was greater with tACS. For features extracted from signals. After tACS intervention, SDNN t = −3.241, 0.002), LF −3.511, 0.001), LFn −3.122, LFn/HFn (−2.928, 0.005), TP −2.706, 0.008), VLF −3.002, 0.004), SD2 −3.594, 0.001) VLI −3.564, showed significant increasing trend, HFn 3.122, SD1/SD2 3.158, 0.002) CCM_1 3.106, 0.003) decreasing trend. only one feature, TINN, upward trend 0.05). other non-significant changes but roughly same as group. Conclusion Both can effective fatigue, is more than tDCS. This study provides theoretical support having alleviating effect use valid objective assessment tool.

Language: Английский

Brain endurance training improves sedentary older adults’ cognitive and physical performance when fresh and fatigued DOI Creative Commons

Jesús Díaz-García,

Tomás García‐Calvo, Christopher Ring

et al.

Psychology of sport and exercise, Journal Year: 2024, Volume and Issue: 76, P. 102757 - 102757

Published: Oct. 2, 2024

Language: Английский

Citations

3
The Detrimental Effects of Mental Fatigue on Cognitive and Physical Performance in Older Adults Are Accentuated by Age and Attenuated by Habitual Physical Activity DOI

Rubén López-Rodríguez,

Christopher Ring, Jesús Díaz‐García

et al.

Journal of Aging and Physical Activity, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 12

Published: Jan. 1, 2025

Objective : Our research objectives were to evaluate the extent which cognitive and physical performance in older adults, when fresh, fatigued vary with age habitual activity. Methods We employed experimental study designs, between- (Study 1: age: 51–64 65–80 years Study 2: activity: active sedentary) within-participants factors test: before task after session: fatigue control task). In testing sessions, participants performed exercise (6-min walk, 30-s sit stand, arm curl) (response inhibition vigilance) tasks a 20-min demanding (time load dual back [TLDB] 2, completed paced breathing (control session) as well TLDB (fatigue session). Ratings of mental exercise-related perceived exertion obtained. Results The elicited state fatigue. Cognitive was worse than task. These impairments moderated by 1) activity 2). Conclusion deleterious effects on accentuated aging attenuated Implications and/or training could mitigate negative adults.

Language: Английский

Citations

0
Mental fatigue recognition study based on 1D convolutional neural network and short-term ECG signals DOI
Ruijuan Chen, Rui Wang, Jieying Fei

et al.

Technology and Health Care, Journal Year: 2024, Volume and Issue: 32(5), P. 3409 - 3422

Published: July 19, 2024

BACKGROUND: Mental fatigue has become a non-negligible health problem in modern life, as well one of the important causes social transportation, production and life accidents. OBJECTIVE: Fatigue detection based on traditional machine learning requires manual tedious feature extraction selection engineering, which is inefficient, poor real-time, recognition accuracy needs to be improved. In order recognize daily mental level more accurately real time, this paper proposes model 1D Convolutional Neural Network (1D-CNN), inputs raw ECG sequences 5 s duration into model, can directly output predicted labels. METHODS: The dataset was constructed by collecting signals 22 subjects at three time periods: 9:00–11:00 a.m., 14:00–16:00 p.m., 19:00–21:00 then inputted 19-layer 1D-CNN present study for classification grades. RESULTS: results showed that able levels effectively, its accuracy, precision, recall, F1 score reached 98.44%, 98.47%, 98.41%, respectively. CONCLUSION: This further improves real-time performance recognizing multi-level electrocardiography, provides theoretical support monitoring life.

Language: Английский

Citations

1
A model for electroencephalogram emotion recognition: Residual block-gated recurrent unit with attention mechanism DOI
Yujie Wang, Zhang Xiu, Xin Zhang

et al.

Review of Scientific Instruments, Journal Year: 2024, Volume and Issue: 95(8)

Published: Aug. 1, 2024

Electroencephalogram (EEG) signals, serving as a tool to objectively reflect real emotional states, hold crucial position in emotion recognition research. In recent years, deep learning approaches have been widely applied research, and the results demonstrated their effectiveness this field. Nevertheless, challenge remains selecting effective features, ensuring retention network depth increases, preventing loss of information. order address issues, novel method is proposed, which named Res-CRANN. proposed method, raw EEG signals are transformed into four dimensional spatial-frequency-temporal information, can provide more enriched complex feature representation. First, residual block incorporated convolutional layers extract spatial frequency domain Subsequently, gated recurrent unit (GRU) employed capture temporal information from neural outputs. Following GRU, attention mechanisms enhance awareness key diminish interference irrelevant details. By reducing or noisy steps, it ultimately improves accuracy robustness classification process. The Res-CRANN exhibits excellent performance on DEAP dataset, with an 96.63% for valence 96.87% arousal, confirming its effectiveness.

Language: Английский

Citations

1
The effect of transcranial electrical stimulation on the relief of mental fatigue DOI Creative Commons
Ruijuan Chen, Lengjie Huang, Rui Wang

et al.

Frontiers in Neuroscience, Journal Year: 2024, Volume and Issue: 18

Published: June 17, 2024

Objective The presence of mental fatigue seriously affects daily life and working conditions. Non-invasive transcranial electrical stimulation has become an increasingly popular tool for relieving fatigue. We investigated whether direct current (tDCS) alternating (tACS) could be used to alleviate the state in a population healthy young adults compared their effects. Methods recruited 10 participants blank control, repeated measures study. Each participant received 15 min anodal tDCS, α-tACS, stimulation. Participants were required fill scale, perform test task collect ECG signals baseline, post-stimulus states. then assessed participants’ subjective scale scores, accuracy HRV characteristics separately. Results found that both tDCS α-tACS significantly ( P < 0.05) reduced improved on group, extent change was greater with tACS. For features extracted from signals. After tACS intervention, SDNN t = −3.241, 0.002), LF −3.511, 0.001), LFn −3.122, LFn/HFn (−2.928, 0.005), TP −2.706, 0.008), VLF −3.002, 0.004), SD2 −3.594, 0.001) VLI −3.564, showed significant increasing trend, HFn 3.122, SD1/SD2 3.158, 0.002) CCM_1 3.106, 0.003) decreasing trend. only one feature, TINN, upward trend 0.05). other non-significant changes but roughly same as group. Conclusion Both can effective fatigue, is more than tDCS. This study provides theoretical support having alleviating effect use valid objective assessment tool.

Language: Английский

Citations

0