*2.3. Experimental Procedures*

All participants visited the Neuromechanics Laboratory for testing. The first 15–20 min was treated as the familiarization session, during which participants had their anthropometry measurements taken and were given an opportunity to ge<sup>t</sup> exposed to the fall safety harness and two trials each of slip and trip perturbations when standing on the treadmill (explained under procedures). The second session, following the familiarization was treated as the experimental testing session. Participants were provided with athletic compression garments, and reflective markers were placed on the lower extremity using a modified Helen Hayes model for the lower extremity [30]. Additionally, participants had four SRS, two each on the anterior and posterior side of each foot–ankle segment, placed in position using a compression sleeve. The SRS arrangemen<sup>t</sup> used in the current study is depicted in Figure 1.

**Figure 1.** Arrangement of SRS and motion capture marker setup to capture and assess sagittal plane ankle kinematics (PF and DF), positioned on a treadmill belt to provide external postural perturbation in the forward and backward direction. SRS: soft robotic sensor. PF: plantarflexion. DF: dorsiflexion.

Participants were then directed to stand on the treadmill, and the fall-arrest harness system was attached to protect from undesired falls due to the treadmill perturbations. Participants were instructed to stand erect, being as still as possible each time before the beginning of slip or trip trials, during which the treadmill belt was turned on and o ff to provide a short brief postural perturbation. The treadmill was operated manually at a preset velocity of 0.67 m/s to provide both slip and trip perturbations. The participant was standing facing backward on the treadmill for slip perturbations (Figure 2) and standing facing forward on the treadmill for trip perturbations (Figure 3). All participants were exposed to one unexpected slip (US) and one unexpected trip (UT) in a counterbalanced order, followed by a series of three expected slips (ES) and a series of three expected trips (ET) in counterbalanced order, with randomized time intervals between the three slip and trip trials. During US and UT trials, participants were not aware of the time of perturbation, which was randomly provided within a 20 s interval to replicate an unexpected postural response through feedback postural control. The timing of the perturbation was random, and the instructions to the participants were always the same for US and ES, during which participants were instructed to stand as erect and still as possible. However, during ES and ET trails, participants were provided a countdown of three seconds before initiation of the treadmill perturbation, to replicate an expected postural response through feedforward postural control. Completion of two unexpected trials (one US and one UT) and six expected trials (three ES and three ET) marked the completion of experimental testing.

**Figure 2.** A sequence of an unexpected slip perturbation with wearable SRS and a motion capture marker system to assess fall detection.

### *2.4. Data Analysis and Statistical Analysis*

Motion capture kinematic data for ankle joint range of motion was determined using a modified Helen Hayes model for the lower extremity through Cortex software. Raw kinematic data were filtered with a low-pass third-order Butterworth filter with a cut-o ff frequency of 30 Hz. The raw capacitance values of the SRS were measured using the 10 Channel Serial Peripheral Interface (SPI) Sensing Circuit in conjunction with the Bluetooth Low Energy (BLE) module, both made by StretchSense. The values were recorded using the proprietary StretchSense BLE iOS application. Due to the nature of the study, every trial produced a unique response for motion capture data and SRS data. In order to conduct the analysis of each trial in a consistent manner, data was only observed from the beginning of the slip or trip perturbation until the joint angle returned to its baseline value prior to the perturbation, which was identified as the "base angle". The absolute max joint angle that occurred in each trial was identified as the "peak angle." Similar peak and base values were collected for the SRS. Each trial consisted of joint angle data collected from the motion capture system and capacitance data collected from the StretchSense module. Peak values were noted for each trial, being either in DF or PF, depending on whether the joint angle increased or decreased in value upon activation of the treadmill perturbation. The difference between the peak value and base value was calculated to indicate the range of motion (ROM) and the capacitance change that occurred for each trial. For motion capture range of motion, negative values indicate PF ROM and positive values indicate DF ROM. Additionally, each trial dataset was scaled down and verified to ensure that the data was adjusted adequately over time and formatted for both motion capture and StretchSense data. For each trial, a model depicting SRS capacitance versus joint angle was created for each foot based on whether the foot initially went into PF or DF (for slip trials and trip trials, respectively). For PF, the posterior SRS was analyzed, while the anterior SRS was analyzed for DF.

**Figure 3.** A sequence of an unexpected trip perturbation with wearable SRS and a motion capture marker system to assess fall detection.

An R (statistical computing software) script was used to generate the linear models and calculate adjusted R-squared and root mean square error (RMSE) values to determine a relative and absolute goodness of fit. A detailed description of the linear model comparing motion capture data and stretch sensor data is provided in Part I and Part II of "closing the wearable gap" papers, recently published from the same researchers in 2018 and 2019, respectively [20,24]. These measures provided metrics to indicate how well the SRS modeled the ankle joint movement during the slip and trip perturbations. For each trial, the base angle (i.e., the joint angle value immediately before perturbation occurred) and peak angle (most extreme angle value in first response) were analyzed for both feet. Additionally, the base and peak capacitance were analyzed for each SRS. The movement that occurred first for each foot (i.e., PF or DF) was noted for each trial. A difference was calculated between all the peak and base values, producing a total joint ROM that occurred during the trial as well as total capacitance change. An example of a bad processing trial that produced bad/poor results and an example of a good processing trial that produced good/grea<sup>t</sup> results are depicted in Figures 4 and 5, respectively. A bad processing trial rendered an R-squared value of 0.7524, and a good processing trial rendered an R-squared value of 0.9781. Finally, additional comparisons such as peak joint angle value comparisons across both feet as an average for each trial and comparisons between males and females were performed to see if there was an observed difference in range of motion and capacitance change and to identify how they affect range of motion as well SRS modelling performance. PF and DF movements were contrasted to see if one type of movement was easier to model with the SRS than the other movement.

**Figure 5.** An example of a good processing trial that produced good/grea<sup>t</sup> result.
