DetectFoG : Detection of Gait Freezing Episodes in Parkinsonian Patients Using Inertial
DetectFoG : Detection of Gait Freezing Episodes in Parkinsonian Patients Using Inertial
Parkinson's disease is the second most common neurodegenerative disease in the world. One of these manifestations is the freezing of gait (FOG) which affects 50 to 80% of Parkinsonian patients. It is defined as a brief and episodic absence or marked reduction in the forward progression of the feet despite the intention to walk. FOG is one of the most disabling symptoms causing a greater risk of falling and a loss of autonomy for these patients. This symptom is little or not dopamine-sensitive and little improved by surgery (deep brain stimulation).
Although this symptom is common and debilitating, it is difficult to assess clinically. The objective assessment of the presence and severity of FOG episodes can be done with tests such as the New-Freezing of Gait Questionnaire (N-FOGQ) with however limitations. Indeed, this filmed examination is scored a posteriori and the accumulation of the administration times which makes it difficult to use in routine clinical practice. To overcome these limitations, the use of a diary completed by the patient himself is a simple alternative to assess this symptom, but studies show that patients abandon this practice in the long term and that it is not used by patients with cognitive impairment.
Recent advances in miniaturization have made it possible to create light and compact sensors to assess these events objectively. Inertial measurement units have been widely used in the literature to detect FOG episodes. The choice of the detection algorithms are a major issue in the scientific community. To date, due to the heterogeneity of the protocols, no method is currently required as a reference.
The objective is to evaluate the accuracy of a new algorithm to detect the number of FOG episodes in Parkinsonian patients. This evaluation will be done on the freeze-inducing walking path.
Inclusion Criteria:
Exclusion Criteria: