# Development of New Soft Wearable Balance Exercise Device Using Pneumatic Gel Muscles
## 2 Materials and Methods
### Data Analysis  
Acceleration data during the single leg stance were measured to assess the effects of the soft wearable balance exercise device and training effects. The acceleration data were collected with a 100 Hz sampling frequency and filtered with a 8 Hz cut-off, zero-phase, low-pass Butterworth filter. An IMU sensor was attached to the posterior trunk at the level of the fifth lumber spine (L5), because this level is close to the COM. The localization of L5 was defined based on two palpation techniques, based on a previous study [28]. The first technique defined L5 from the iliac crests as reference points in the standing position. The second technique defined L5 from the inferior margins of the posterior superior iliac spines as reference points in the standing position.  
The peak acceleration value for the medio-lateral direction (Ax), vertical direction (Ay), and antero-posterior direction (Az) were measured to determine whether the wearable balance exercise device was able to induce perturbation in participants. Previous studies reported that postural control responses against unexpected perturbations occurred between +100 ms and +400 ms from the occurrence of the perturbation [29; 30]. In addition, it has been reported that unexpected perturbations  
Figure 6: Subject’s measurement task using wearable balance exercise device.  
caused a COM shift in the direction of the perturbation [23; 31]. Thus, we measured the same- and opposite-side directions of perturbation peak acceleration values as perturbation peaks (p-A; p-Ax, p-Ay, and p-Az) and response peaks (r-A; r-Ax, r-Ay, and r-Az), respectively, in the reactive postural control assessment session from 0 to +400 ms in relation to the perturbation time. Specifically, p-Ax was the dominant leg side direction, and p-Ay was the inferior direction, because the device caused bending of the dominant leg side trunk by PGM in the session. Regarding p-Az, the device had a weaker effect on the Az direction because this device mainly caused lateral side trunk bending. So, p-Az was seemingly more affected by standing position than PGMs. Thus, we measured the first peak of Az as the perturbation direction during this session. The baseline for the reactive postural control assessment session for the acceleration value was calculated in the interval from \(-\)500 ms to \(-\)10 ms before the moment of pushing the PGM contraction button. (b-A; b-Ax, b-Ay, and b-Az). The baseline peak acceleration value was calculated as an absolute value. We also set the perturbation period from the moment of pushing PGMs contraction button to 300 ms. Response period was set to 400 ms from the moment of p-A. We compared baseline peak acceleration, perturbation peak acceleration, and response peak acceleration. In addition, we compared the respective times (Tp-A; Tp-Ax, Tp-Ay, and Tp-Az. Tr-A; Tr-Ax, Tr-Ay, and Tr-Az) between each direction.  
Moreover, we compared the root mean square (RMS) values of Ax, Ay, and Az in the pre- and post-test sessions to assess the effects of exercise. The acceleration data from 10 to 20 s of pre- and post-test were used for RMS calculation.  
The normal perturbation of the data was verified using the Shapiro-Wilk test. A one-way repeated measures analysis of variance and multiple comparisons (Shaffer's modified sequentially rejective Bonferroni procedure) were used to compare b-A, p-A, and r-A. Paired \(t\)-tests were used to compare Tp-A and Tr-A, as well as RMS between pre-test and post-test. All statistical analyses were performed with R version 2.8.1 (CRAN, freeware). Data were presented as mean \(\pm\) standard deviation. Statistical significance was set at \(p<0.05\).