# Validation of a Wearable IMU System for Gait Analysis: Protocol and Application to a New System
## 2 Materials and Methods
### Experimental Setup for Validation
If this is taken into account, the choice to increase the number of trials to have a larger statistical sample conflicts with the repeatability and the precision of data. We have chosen to define four trials in the protocol because it was compatible with healthy volunteer time management and the time available for the GA evaluation without creating problems for patient examination planning. We have analyzed 40 datasets (10 subjects \(\times\) four trials = 40 datasets). The recording of data must be simultaneous and synchronized with the device and the motion capture system. The synchronizing trigger could be hardware, software, or functional (for example, making the subject execute a standard start/end movement as a jump). The sampling rate for data collection from the two systems has to be coherent to allow data comparison. Contextual video recording is adopted for a further reference on qualitative and quantitative information (e.g., side of the step, number of steps, step duration). The operator verifies if the dynamometric force platforms are activated correctly. The subject executes each test session four times, walking with his/her shoes. There is a rest period of a few minutes between one session and the next. The step length S is self-selected and the walking time is not a constant depending on the subject's speed. For each task, an expert medical operator registers the test execution time (using a stopwatch), the number of steps, and the first foot of support (left or right) on a paper report. These values, together with those generated by the GA report, constitute the reference data set. _Data analysis._ Only coherent measurements have to be analyzed and compared. The comparison between the wearable system and the gold standard GA is done according to the analysis of the following parameters: (a) number of steps and related limb (left/right); (b) basic temporal parameters: walking time, step times (stance/swing), stride time, cadence; (c) basic spatial parameters: step length (single, average, right/left limb), walking distance (if possible in the laboratory setup). When the optoelectronic GA analysis standard report is generated, it has to be remembered that GA provides data of a single step or stride (usually the central one in the recorded trial selected by the operator or automatically by the system from the Ground Reaction Force data). When comparing data, a blind data analysis approach is preferable to avoid operator's bias in data processing and interpretation. This ensures better impartiality in verifying the matching of the results. Access to the data output of the GA test is allowed to the operators in charge of the processing of data generated by the wearable device only when data elaboration has been completed. We used statistics for data analysis based on absolute and absolute percentage error \(\varepsilon\) (computed as the difference between corresponding parameters assuming the optoelectronic GA as the true reference). A classification criterion of acceptability is used to identify the outcome of the measurement [24]. The adopted criterion is based on four categories defined by standard statistical thresholds for significance analysis [30], i.e., the commonly used values of 5%, 10%, and 20%:  
1. Excellence: for \(\varepsilon_{\%}<5\%\)
2. Good: if 5% \(\leq\varepsilon_{\%}<10\%\)
3. Sufficient: if 10% \(\leq\varepsilon_{\%}<20\%\)
4. Not acceptable: in case of \(\varepsilon_{\%}\geq 20\%\)  
The reference threshold of the mean absolute percentage error in accuracy (\(\varepsilon_{\%}\)) of step length and distance is usually fixed at 5% [19]. Starting from this value and considering the setup, this study uses the reliability assessment grid shown in Table 2.  
The proposed criterion has only been applied to the absolute percentage error. This implies a more strict evaluation of method reliability because the relative accuracy percentage error could introduce some compensations (having both positive and negative values).