Two independent raters clinically assessed all walking trials by examining the raw video recordings and the optoelectronics-based lower limb motion track replays. The two raters each gave judgements on whether a trial contained freezing and when the freezing occurred. We also adopted a freezing index (FI) approach to objectively determine and quantify freezing events21 and deposited the code for computing FI from 3D optoelectronics data on https://github.com/zixiao-yin/ecogFog. Briefly, we first transformed the coordinate data recorded by the optoelectronic sensors to acceleration data by calculating differencing twice (Python function diff). Spectrum analysis was then performed on the transformed acceleration data with respect to the forward walking direction using the fast Fourier transform.13 The FI was computed as the ratio of power between the ‘freezing band’ (3–8 Hz) and the ‘locomotion band’ (0–3 Hz)21 in a 6 s-sliding window centred in t with a step size of 0.1 s. The final FI was the average of eight sensor channels that were least contaminated (four on each side, including foot, shank, thigh and waist). A ‘freezing threshold’ was set to ‘3’.21 Notably, because
