Yukihiko Ushiyama

Influence of muscular fatigue on skiing performance during parallel turns

Muscular fatigue and muscle-activation patterns during a skiing demonstration (down a coarse around 4000 m long) was evaluated. Nine subjects participated in skiing trials and pre-training with a squat exercise. Surface electromyogram (SEMG) signals from the agonist and antagonist muscles around the knee at certain knee-joint angles were recorded. The SEMG signals showed that experienced skiers maintained their posture regardless of muscle fatigue by means of sustained muscle contractions in accordance with the change in inclination of the slope. In contrast, intermediate skiers did not maintain their posture (because of muscle fatigue) and distributed their strength over muscles to co-contract with each other. It is concluded from this result that the influence of muscle fatigue on skiing performance is related to skill level.1

Evaluation of fatigue using heart rate variability and myoelectric signals during skiing

We studied the change in functional activities during skiing exercise for a whole day, in terms of the interactions between cardiovascular and neuromuscular activities with the progression of fatigue. To evaluate functional activities at each phase, we developed a radio controlled remote data acquisition system for measuring multichannel biosignals. Then we used the wavelet analysis for analyzing the details in the heart rate variability. Based on the previous results, we proposed a scatter graph between an autonomic nervous activity related index and a muscular fatigue related index. The scatter graph was effective as a tool for a snapshot evaluation of fatigue or degeneration of functional activities during long-term physical exercise.

Snapshot evaluation of fatigue during skiing exercise

We have measured and analyzed the heart rate variability (HRV) and myoelectric (ME) signals during skiing exercise for a whole day. To realize snapshot evaluation of functional activities for this long-term exercise, we developed a radio controlled remote data acquisition system, and then evaluated data using spectrum analysis. We compared the spectrum of the HRV between skiing and ski lift riding, within the target frequency bands, using the wavelet analysis. During skiing, we estimated the amplitude and frequency indices as ME parameters. Then we applied the principal component analysis and the ARX model to represent the changes in functional activities. The results quantitatively showed the time-varying features of dominant frequency components in HRV and the relationship between cardiovascular and muscular activities with the progression of fatigue.

Estimating the spin of a table tennis ball using Inverse Compositional Image Alignment

In this paper, we propose a method for estimating the rotational velocity of a table tennis ball with Inverse Compositional Image Alignment, ICIA. Assuming orthogonal projection of the camera, we derive an update rule for the motion parameters. Because of the precomputation of the Hessian matrix in ICIA and the simplifying assumptions, the motion parameters estimation at each frame is very fast. We evaluate results for measuring the spins in a synthesized sequence, as well as in real image sequences of table tennis rallies.

Fatigue assessment during exercise using myoelectric signals and heart rate variability

A practical fatigue assessment during repetitive long-term exercise is presented by using myoelectric (ME) signals and heart rate variability (HRV). We developed a radio-controlled remote data acquisition system and used a correlation coefficient of ME parameters and a ratio of dominant frequency components in HRV. We showed the applications to skiing exercise and cycle ergometer exercise.

Snapshot evaluation of fatigue using heart rate variability and superimposed M-waves of myoelectric signals during skiing exercise

We simultaneously measured the heart rate (HR) and myoelectric (ME) signals during a skiing exercise for a whole day. To realize a snapshot evaluation of fatigue for this long-term exercise, biosignal processing should be designed to estimate the target factors from biosignals and to deal with biosignals measured at a restricted condition. We accumulated the power spectrum of the HR time series within the target frequency bands determined by the results of wavelet analysis. On the other hand, the evoked potential approach was used for evaluating muscle fatigue via ME signals. The accumulated power spectrum of the HR time series changed periodically during skiing and ski-lift riding. Furthermore, a muscle fatigue index and the features of the HR time series became prominent towards the final trial of the day. As a result, we could investigate fatigue at the required times based on the relationship between the time-varying behavior of HR time series and the muscular fatigue index, during long-term skiing exercise.