A simple method to assess freezing of gait in Parkinson's disease patients

Using EEG spatial correlation, cross frequency energy, and wavelet coefficients for the prediction of Freezing of Gait in Parkinson's Disease patients

“…Wavelet energy is computed on each retained wavelet scale (c 6 , d 6 3 ) by squaring and summing the wavelet coefficients of the decomposed level [5]. In this study, wavelet cross frequency energy ratios (ER) (δ /β ) and (θ /β ) were observed and selected as features since they are part of major frequency bands of oscillation in the basal ganglia which may have a functional role in movement [14].…”

“…Several techniques have been explored to detect FOG such as using electromyogram (EMG) [3], acceleration sensors [4], functional neuroimaging [1] and electroencephalogram (EEG) [5]. Amongst these approaches, EEG offers predictive capability due to its greater temporal resolution and ability to measure dynamic physiological change.…”

Foot Pressure Wearable Sensors for Freezing of Gait Detection in Parkinson’s Disease

“…The analysis of the pressure distributions and pressure-related parameters under feet measured by the sensor insoles can indeed differentiate between FoG episodes happening at step initiation or with complete motor blocks (i.e., the absence of effective steps), which the accelerometer-based algorithm failed to recognize. To the best of our knowledge, only one other study tested the use of pressure sensors to detect FoG episodes in PD [20]. Even if they used a different approach in data analysis and not a 3D accelerometer to complement the pressure data, the authors demonstrated that their system was sensitive to various freezing with results obtained from only 24 FoG episodes.…”

“…A further development of this approach called for the use of both accelerometer and gyroscope signals collected from sensors mounted on the lateral aspect of tibia and segmented on a gait cycle basis. Segmented signals were used to feed an algorithm based on Pearson's correlation coefficient to: (i) separate epochs of "normal" strides from those that differ significantly from the so-called "representative" stride; and (ii) classify the latter group based on the frequency content of the acceleration signals and on the spatio-temporal parameters of gait estimated fusing accelerometers and gyroscopes measures [20,21]. This approach was only validated for people with PD displaying a dominantly normal gait pattern.…”

“…All the reported approaches are applicable to identify FoG episodes while walking and could then fail when a lack of or small movements occur. Indeed, different subtypes and features of FoG can be observed [20,21]: e.g., FoG with legs trembling and FoG with complete motor blocks in absence of effective steps. In this perspective, Center Of Pressure (COP) trajectories could be informative about the intention of movement [21,22], especially when looking at the frequency domain.…”