A New Software for Quantifying Motor Deficit After Stroke: A Case–Control Feasibility Pilot Study - Gutiérrez Zúñiga, Raquel; Alonso de Leciñana, María; Díez, Alejandro; Torres Iglesias, Gabriel; Pascual, Alejandro; Higashi, Ariaki; Rodríguez Pardo, Jorge; Hernández Herrero, David; Fuentes, Blanca; Díez Tejedor, Exuperio (Frontiers in Neurology, 2021)
Introduction: The degree of disability after stroke needs to be objectively measured to implement adequate rehabilitation programs. Here, we evaluate the feasibility of a custom-built software to assess motor status after stroke. Methods: Prospective, case-control pilot study comparing stroke patients with healthy volunteers. A workout evaluation that included trunk and upper limb movement was captured with Kinect® and kinematic metrics were extracted with Akira®. Trunk and joint angles were analyzed and compared between cases and controls. Patients were evaluated within the first week from stroke onset using the NIHSS, FMA and mRS scales; the relationship with kinematic measurements was explored. Results: 37 patients and 33 controls were evaluated. Median (IQR) NIHSS of cases was 2 (0-4). The kinematic metrics that showed better discriminatory capacity were body sway during walking (less in cases than in controls, p= .01) and the drift in the forearm-trunk angle during shoulder abduction in supination (greater in cases than in controls, p = .01). The body sway during walking was moderately correlated with NIHSS score (Rho =-.39; p = .01) but better correlated with mRS score (Rho = -.52; p < .001) and was associated with the absence of disability (mRS 0-1) (OR= .64, p= .02). The drift in the forearm-trunk angle in supination was associated with the presence of disability (OR= 1.27, p =.04). Conclusion: We present a new software that detects even mild motor impairment in stroke patients underestimated by clinical scales but with an impact in the patient functionality.