論文

We examined muscle stiffness at various pedaling rates under conditions of constant power output. Eight healthy young participants pedaled a cycle ergometer at a power output of 47 W. The combinations of pedaling rate and workload were 40 revolutions per min (rpm) and 11.7 N, 60 rpm and 7.8 N, and 80 rpm and 5.9 N, respectively. One electrical stimulus per two pedal rotations was applied to the vastus lateralis muscle at a crank angle of 30° in the down phase. Mechanomyograms (MMGs) were measured using a capacitor microphone, and the evoked MMG was extracted. An evoked MMG system was identified, and the coefficients of the denominator of the transfer function were used to estimate stiffness and viscous coefficient of the muscle. Muscle stiffness was 236–705 Nm−1, and was proportional to the pedaling rate when power output was held constant, while the viscous coefficient did not change from approximately 15 Nm−1s. In conclusion, our findings demonstrate that stiffness of the vastus lateralis muscle increases with increasing pedaling rate under conditions of constant power output, while the viscous coefficient does not change.

© 2020 The Author(s). Medial gastrocnemius muscle stiffness was estimated using a system identification technique. The medial gastrocnemius muscle was electrically stimulated using surface Ag-AgCl electrodes and the center of pressure fluctuation in the forward-backward direction was measured with a force plate. Electrically induced fluctuation of the center of pressure was classified according to the displacement and velocity of the center of pressure. The classified steps of displacement and velocity were 0.2 cm and 0.2 cm/s, respectively. The ranges of the classes were ±0.15 cm and ±0.15 cm/s. The classified fluctuations were synchronously averaged and the averaged fluctuation was regarded as an output signal of the transfer function from the electrical stimulation to the fluctuation. The transfer function was identified as an estimate of muscle stiffness using a singular value de-composition method. The average muscle stiffness of eight young male participants ranged from 56.7 to 75.9 N/m. Muscle stiffness was high when the displacement of the center of pressure was positive and the velocity was negative. These characteristics resembled the preceding 0.3 s of the electromyogram. This preceding high muscle activity probably contributed to muscle stiffness. Muscle stiffness was well approximated with a multiple linear regression plane, in which the explanatory variables were the displacement and velocity of the center of pressure.

Standing posture is stabilized by a control mechanism involving the stiffness of the ankle joint. Ankle joint stiffness has previously been studied by measuring the electrically induced fluctuation of the center of pressure. However, the fluctuation is a complex output of a neuromuscular system and a measurement system, and its mechanism has therefore remained unclear. The purpose of this study was to construct a model of the process leading from electrical stimulation to floor reaction torque and to estimate net ankle joint stiffness. The model consisted of an inverted pendulum with a Hill-type muscle model and was described by a state equation that was solved using the Runge‒Kutta method. Some of the model parameters were derived from the physical characteristics of the participants. Unknown parameters were estimated using a nonlinear least squares method by comparing the model torque with the experimental torque. The experimental torque was well reproduced using the model. The stiffness of the ankle joint (passive and active) was 627–944 Nm/rad, which was able to stabilize the standing posture.

The purpose of this study was to clarify the effect of reducing somatosensory feedback by foot cooling on the medial gastrocnemius muscle. Using a system identification technique, we estimated the natural frequencies of the muscle and the ankle joint. The natural frequencies are proportional to the square root of the muscle and joint stiffnesses and indicate the frequency characteristics of quiet standing. We measured the center of pressure (COP) of eight young volunteers aged 22–24 years before and after foot-cooling by immersing the feet in water with ice. Electrical stimulation was applied to the medial gastrocnemius muscle, and electrically induced COP fluctuation was extracted using a Kalman filter and synchronously averaged based on the stimu-lation. The synchronously averaged COP fluctuation was considered an impulse response, and the transfer function was identified using a singular value decomposition method. The natural frequencies were estimated from the poles of the transfer functions. The natural frequencies of the muscle before foot cooling ranged from 1.96 to 3.09 Hz, and those after foot cooling decreased to a range of 1.40 to 2.19 Hz. There was a significant difference (p < 0.01) between the natural frequencies before and after foot cooling. The natural frequencies of the ankle joint tended to decrease after foot cooling, although the difference was not significant. The natural frequency of the medial gastrocnemius muscle decreased significantly when foot cooling reduced somatosen-sory feedback in the feet.

We investigated a system identification method for modeling the standing posture without external perturbation. Assuming that postural sway during quiet standing is caused by internal white noise, the method adopts an autocorrelation matrix consisting of body position and velocity parameters. We showed that the method can be applied to center-of-mass fluctuation measurement data. Since we used only a force plate to minimize the burden on the subjects, the velocity could not be measured directly. Therefore, we first demonstrated through simulation that ankle joint stiffness can be estimated by numerically deriving the velocity from the displacement. The velocity was calculated using the central difference approximation, and the ankle stiffness estimation error was obtained. The system identification method was then applied to the center-of-mass measurement data, and the ankle stiffness was estimated. Simulations showed that even when the velocity was calculated through numerical differentiation, the ankle joint stiffness could still be estimated with an accuracy of less than 1% error. The ankle stiffness estimated from the measured center of mass was slightly higher than the gravitational torque coefficient, but lower than that obtained in our previous electrical stimulation study (Uchiyama T: Adv Biomed Eng. 13, 223‒229, 2024). This suggests that the control method for ankle stiffness may depend on the presence or absence of external disturbances.

最大エントロピー法を用いて，生体の31P-NMRスペクトルを高分解能に推定することができることを報告した．（7頁）

最大エントロピー法を用いて細胞内カリウムイオン濃度を39K-NMRで高分解能に推定できることを報告した．（6頁）

複数の線形予測に基づくスペクトル推定法をラット灌流心の31P-NMRスペクトルの推定に適用し，評価して報告した．（9頁）

特異値分解を伴う線形予測法をMRI画像の推定に適用することにより，トランケーションアーティファクトの影響を受けない画像を復元することができることを報告した．（9頁）

ホルター心電図をテンプレートの自動更新と折れ線近似の残差を圧縮する方法で圧縮することにより，ニーズに応じた圧縮率およびビットレートで圧縮することができる方法を提案した（5頁）．

ホルター心電図を折れ線近似と残差を圧縮することにより，高い圧縮率で圧縮できることを報告した．（8頁）

肘関節屈筋について，筋活動度が一定のときの関節角度とトルクの関係をニューラルネットワークを用いて推定した．その特性は，筋骨格系の構造の影響を強く受けることを報告した．（8頁）

肘関節の屈筋および伸筋について，筋活動度が一定のときの関節角度とトルクの関係をニューラルネットワークを用いて推定した．その特性は，筋骨格系の構造の影響を強く受けることを報告した．（12頁）

複数の指標を用いることで，リアルタイムで回内および回外動作を含む上肢の運動を計測することができる方法を開発し，報告した．（6頁）

皮膚振動刺激によって義手の開閉角度をフィードバックするシステムを開発し，フィードバックシステムの有効性について報告した．（6頁）

等速度で肘関節を伸展する動作について，筋活動度を一定に維持しているときの関節角度とトルクの関係を調べ，運動時にもバネに類似する特性をもつことを報告した．また，伸展速度とトルクの関係は，Hillの式の拡張で説明できることを報告した．(11頁）