Motion prediction using brain waves based on artificial intelligence deep learning recurrent neural network.

Electroencephalogram (EEG) research has gained widespread use in various research domains due to its valuable insights into human body movements. In this study, we investigated the optimization of motion discrimination prediction by employing an artificial intelligence deep learning recurrent neural network (gated recurrent unit, GRU) on unique EEG data generated from specific movement types among EEG signals. The experiment involved participants categorized into five difficulty levels of postural control, targeting gymnasts in their twenties and college students majoring in physical education (n=10). Machine learning techniques were applied to extract brain-motor patterns from the collected EEG data, which consisted of 32 channels. The EEG data underwent spectrum analysis using fast Fourier transform conversion, and the GRU model network was utilized for machine learning on each EEG frequency domain, thereby improving the performance index of the learning operation process. Through the development of the GRU network algorithm, the performance index achieved up to a 15.92% improvement compared to the accuracy of existing models, resulting in motion recognition accuracy ranging from a minimum of 94.67% to a maximum of 99.15% between actual and predicted values. These optimization outcomes are attributed to the enhanced accuracy and cost function of the GRU network algorithm's hidden layers. By implementing motion identification optimization based on artificial intelligence machine learning results from EEG signals, this study contributes to the emerging field of exercise rehabilitation, presenting an innovative paradigm that reveals the interconnectedness between the brain and the science of exercise.

Electromyography comparison of normal chair-desk system and assistant chair-desk system on fatigue.

[Purpose] This study was designed to test the effects of the Assistant Chair-Desk System (ACDS), which can reduce the forward tilt of the neck and trunk and the level of fatigue during long lasting study in the sitting position. [Subjects] Fourteen middle school students and 14 college students of mixed gender participated in this study. [Methods] Fatigue level, the trapezius muscle, and the forward tilt angle of the head and trunk as well as distance factors were assessed before after using a normal chair-desk system (NCDS) and the ACDS for 120 minutes. [Results] There was an interaction effect in the angle and length of the neck from the sitting posture changes after 2 hours of studying using the NCDS and ACDS. There were also significant differences in the fatigue levels, hip joint angles and the lengths from the head according to the main effects of the chair-systems. [Conclusion] The studying position while using the ACDS was determined to prevent significant fatigue levels of the muscle and body, provide support to the head, by limiting the forward movement of the neck, and prevent forward tilt of the neck and trunk, by enabling the target point and gaze to be closer to the horizontal direction.

A biomechanical assessment of the sliding motion of curling delivery in elite and subelite curlers.

The present study examined the technical characteristics of sliding performance from push-off until stone release in curling delivery. Five elite performance level curlers (> 7 years experience) and five subelite level curlers (< 3 years experience) were analyzed during the action of delivery of a curling stone. The joint angles, angular velocities, and moments of the body center of mass (COM) were determined based on three-dimensional kinematic data. The plantar pressure data were measured using a validated in-shoe system. The results indicated that the gliding time and horizontal velocity of the mass center of the body during the sliding phase were not significantly different between the elite and subelite groups. However, there were significant differences in the gliding distance and the rate of changes in velocity profiles of body COM between the two groups. The moment of the body COM from its relative position to the ankle of the support limb in the anterior/posterior direction was positive in elite curlers and negative in subelite curlers. In addition, larger ankle dorsiflexion and greater contact area of the sliding foot were observed in elite curlers. These data suggest a superior ability of elite curlers to maintain a regulated movement speed and balance control during the performance of a curling stone delivery.

Coordinative and limb-specific control of bimanual movements in patients with Parkinson's disease and cerebellar degeneration.

The present study examined the effects of basal ganglia and cerebellar pathology on bimanual coordination using patients with Parkinson's disease (PD) and cerebellar dysfunction (CD). Twenty patients with idiopathic PD (10 untreated early and 10 advanced PD), 10 patients with cerebellar degeneration, and 11 normal subjects were instructed to perform in-phase and anti-phase bimanual coordination movements. The results indicated that while the quality of coordinated bimanual movements in untreated early PD and CD patients was not significantly different from that of normal controls, advanced PD patients exhibited reduced synchronized coordination during the faster anti-phase mode. This suggests that the observed bimanual coordination abnormalities in PD are not an early sign of the pathophysiology of the disease, and cerebellar degeneration may have minimal consequences on synchronized coordination between the limbs. In terms of the parameterization of individual limb movements, CD patients showed a tendency for hypermetric impairments with more irregular movements, while PD patients exhibited relatively slower limb movements and lower amplitudes than normal controls. Overall, the current data provide evidence of the specific functions of different neural structures involved in the pathological process of PD and CD on bimanual coordination.