Finally, some objective diagnosis of stroke deficits. How fucking long before it gets to your stroke hospital? Then your therapists and doctors can quit guessing about what needs to be done. It is completely up to YOU to get this in your hospital, your hospital will do nothing. I bet none of these are sensitive enough to measure finger deficits.
A New Software for Quantifying Motor Deficit After Stroke: A Case–Control Feasibility Pilot Study
Raquel Gutiérrez Zúñiga1, 
María Alonso de Leciñana1*, 
Alejandro Díez2, 
Gabriel Torres Iglesias1, 
Alejandro Pascual3, Ariaki Higashi2, 
Jorge Rodríguez Pardo1, David Hernández Herrero4, Blanca Fuentes1 and 
Exuperio Díez Tejedor1*- 1Department of Neurology and Stroke Center, Hospital La Paz Institute for Health Research-IdiPAZ, La Paz University Hospital, Universidad Autónoma de Madrid, Madrid, Spain
- 2System Friend Inc., Hiroshima, Japan
- 3Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain
- 4Department of Rehabilitation, Hospital La Paz Institute for Health Research-IdiPAZ, La Paz University Hospital, Universidad Autónoma de Madrid, Madrid, Spain
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: This is a 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 National Institutes of Health Stroke Scale (NIHSS), Fulg-Meyer Assessment (FMA), and modified Rankin Scale (mRS) scales; the relationship with kinematic measurements was explored.
Results: Thirty-seven 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 = 0.01) and the drift in the forearm–trunk angle during shoulder abduction in supination (greater in cases than in controls, p = 0.01). The body sway during walking was moderately correlated with NIHSS score (Rho = −0.39; p = 0.01) but better correlated with mRS score (Rho = −0.52; p < 0.001) and was associated with the absence of disability (mRS 0–1) (OR = 0.64; p = 0.02). The drift in the forearm–trunk angle in supination was associated with the presence of disability (mRS >1) (OR = 1.27; p = 0.04).
Conclusion: We present a new software that detects even mild motor impairment in stroke patients underestimated by clinical scales but with an impact on patient functionality.
Introduction
Stroke is the most prevalent cause of disability worldwide. Two of three stroke survivors will develop deficits that will cause high healthcare and social costs (1, 2). Apart from speech, visual, or cognitive deficits, one of the most important components of stroke-related disability is motor function impairment. Even mild deficits that may not be detected in routine clinical evaluation may significantly reduce patient's quality of life by interfering with the activities of daily living and their capacity to return to work. For these reasons, it is important to reliably measure these deficits and be able to correlate them with the degree of disability in order to implement adequate and personalized rehabilitation programs.
Motion capture systems (MCS) have been used to assess motor function in different neurological conditions with promising results (3–7). The main advantages are their low cost and relative ease of use. The most commonly used system is Microsoft Kinect®, which is a portable and marker-free motion capture system that uses an infrared light and a deep sensor to create a three-dimensional reconstruction of the human body and detect its movements. Kinect® results are concordant with marker-based systems which are the gold standard for motion analysis (8). In combination with specific software, Kinect® can be used for rehabilitation purposes (9). Previous studies have evaluated the feasibility of this system for gait assessment in multiple sclerosis or Parkinson disease (5, 7, 10) and for upper extremity motor function evaluation in muscle diseases (3, 4).
The use of kinematic metrics as a reliable measure of motor function for rehabilitation purposes in stroke patients is currently recommended (11). However, only few studies evaluate the usefulness of kinematic measurements to analyze motor deficit after stroke in order to help physicians to objectively measure patient's deficits. One example is the KINARM system that evaluates upper limb function in stroke patients (12, 13). Nevertheless, this system is complex and requires an exoskeleton, making it unsuitable to be used in routine clinical practice. Recent works suggest that Kinect® and virtual reality systems can effectively guide rehabilitation workouts in stroke patients (9, 14), but few studies analyze the usefulness of the Kinect® system for assessing poststroke functional status. One includes gait assessment (6), while others analyze reaching tasks in poststroke patients and show good concordance with specific clinical scales (15, 16). However, to our knowledge, a complete workout design to test the global function in poststroke patients with Kinect® has not been studied, and there is no information available about the potential relationship between the kinematic measures and disability after stroke.
Although Kinect® is becoming widely used, each research group uses their own software for the kinematic analysis. The Akira® software (Akira, System Friend Inc.) is a custom-built software developed to be used with Kinect® without body markers, which reconstructs a three-dimensional avatar of the human body and obtains kinematic metrics from body movement records.
Our main aim is to evaluate the usefulness of Microsoft Kinect® along with the software Akira® for an objective motor status evaluation after stroke. The secondary objective is to explore the relationship between kinematic metrics provided by the software and functional status after stroke.
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