have proposed a technique to identify FOG episodes based on the f

have proposed a technique to identify FOG episodes based on the frequency properties of leg vertical accelerations. The approach is based on the hypothesis that FOG occurrences are associated to trembling motion, which affect limb acceleration signal. They have introduced the so-called freeze index (FI): the ratio between the sellekchem signal (limb acceleration) power in the ��freeze�� band and the signal power in the ��locomotor�� band. The FI method was validated using one to seven accelerometers mounted on patients with satisfactory detection results [19]. In the present paper we propose a complementary index in order to take into account both trembling and festination situations. Our objective is to anticipate the occurrence of FOG episodes in order to propose a robust solution for real-time control of assisted devices. We believe, festination is one of the FOG expressions and precedes most of gait interruptions and is an interesting marker of gait modification. Furthermore we intend to propose a solution based on a minimal number of embedded sensors and detection algorithms for future real-time applications.In Section 2 we recall the definition of FI and introduce our FOG criterion (FOGC). In Section 3 we present the inertial sensor on which our solution is based and we describe the experimental setup. In Section 4 the results are described and discussed.2.?Freezing of Gait DetectionMoore et al. introduced the freeze index (FI) as the power of the considered body segment acceleration signal in the ��freeze�� band (3�C8 Hz) divided by the power of the signal in the ��locomotor�� band (0.5�C3 Hz) [18�C20]. For each instant t, FI(t) is defined as the square of the area under the power spectra of a 6 s window of data (centered at time t) in the ��freeze�� band, divided by the square of the area under the power spectra in the ��locomotor�� band. The width of the sliding window is based on FOG duration. It has been determined that the optimal window width has to approximately be twice the duration of the shortest FOG event to be detected. Increasing the window size reduces the sensitivity of the FI, acting as a low-pass filter by not identifying the short-duration freeze events. A FI threshold is chosen such that FI values above this limit are designated as FOG. In their article, Moore et al. have chosen the threshold as the mean plus one S.D. of the peak FI from nine epochs of volitional standing.Here, we introduce a new approach for the observation of gait changes and the detection of FOG events, the so-called FOG criterion (FOGC). FOGC is based on the continuous evaluation of two gait parameters: cadence and stride length. Cadence during festination in PD patients reported values less than 3 Hz (2.8 Hz [S.D.0.2]) [5]. Our hypothesis is that, before a FOG event occurs, the cadence should increase whereas the stride length decreases (festination).

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