Induced effects of electrical muscle stimulation and visual stimulation on visual sensory reweighting dynamics during standing on a balance board.

Providing instruction cues on body motions using stimulations has the potential to induce sensory reweighting dynamics. However, there are currently very few quantitative investigations on the difference in the induced effects on the sensory reweighting dynamics between stimulation methods. We therefore investigated the difference in the induced effects of electrical muscle stimulation (EMS) and visual sensory augmentation (visual SA) on sensory reweighting dynamics during standing on a balance board. Twenty healthy participants controlled their posture to maintain the board horizontally in the balance-board task, which included a pre-test without stimulation, a stimulation test, and a post-test without stimulation. The EMS group (n = 10) received EMS to the tibialis anterior or soleus muscle based on the board tilt. The visual SA group (n = 10) received visual stimuli via a front monitor based on the board tilt. We measured the height of the board marker and calculated the board sway. Before and after the balance-board task, the participants performed static standing with their eyes open and closed. We measured postural sway and calculated the visual reweighting. The visual reweighting showed a strong negative correlation with the balance board sway ratio between the pre- and stimulation tests in the EMS group and a strong positive correlation with that in the visual SA group. Moreover, for those who reduced the balance board sway in the stimulation test, the visual reweighting was significantly different between the stimulation methods, demonstrating that the induced effect on sensory reweighting dynamics is quantitatively different depending on which method is used. Our findings suggest that there is an appropriate stimulation method to change to the targeted sensory weights. Future investigations on the relationship between sensory reweighting dynamics and stimulation methods could contribute to the proposal and implementation of new training methods for learning to control the target weights.

Force Control on Fingertip Using EMS to Maintain Light Touch.

Light touch on a rigid surface with minimal force below a specific threshold reduces postural sway by providing additional sensory cues from the fingertips. The feasibility of maintaining light touch depends on subject characteristics and task difficulty. Therefore, we introduce a method of maintaining light touch by using electrical muscle stimulation (EMS). We applied it in a single-leg standing task involving healthy adult subjects. The subjects stood upright in a single-leg stance on a firm surface and on foam rubber (FR), respectively, under three conditions: no touch (NT, NT-FR), light touch without EMS (LT, LT-FR), and light touch in which EMS was applied based on the contact force (LT-EMS, LT-EMS-FR). The results showed that the force control by EMS helped maintain light touch and reduce postural sway compared with the no-touch condition. The amplitude of postural sway under the touch condition with EMS was equivalent to that under the touch condition without EMS.

Correction of Electrode ID Configuration based on Distribution of Surface EMG Features.

Surface EMG (sEMG) signals are useful for estimating the motion or exercise of users. Wireless-type sensor electrodes, which are placed on multiple parts of the body and send the measured signals to a server, have recently become commercially available. With many estimation algorithms, the relationships between the sensor IDs and the body parts they are placed on (ID configuration) are expected to be fixed between the calibration and estimation phases. If the ID configuration is changed after the calibration phase, the estimation accuracy tends to dramatically decrease. Since it is inconvenient for users to check the ID configuration every time, we developed a method to correct the electrode ID configuration on the basis of the distribution of sEMG features. Using open data, we investigated the feasibility of our method by shuffling the order of sEMG signals. The results showed that the method was able to correct the ID configuration and restore the estimation accuracy to close to that of the calibration.