Chidozie Emmanuel Mbada - Department of Health Professions, Faculty of Health and Education, Manchester Metropolitan University, Manchester, United Kingdom.
Emmanuel Oluwatosin Abata - Department of Medical Rehabilitation, College of Health Sciences, Obafemi Awolowo University, Ile-Ife, Nigeria.
Omoniyi Ayokunle Ojapinwa - Department of Medical Rehabilitation, College of Health Sciences, Obafemi Awolowo University, Ile-Ife, Nigeria.
Saturday Nicholas Oghumu - Department of Physiotherapy, Faculty of Allied Medical Sciences, College of Medical Sciences, University of Calabar, Calabar, Nigeria.
Adekola Ademogoyegun - Department of Physiotherapy, Osun State University Teaching Hospital, Osoggbo, Nigeria.
Francis Fatoye - Department of Health Professions, Faculty of Health and Education, Manchester Metropolitan University, Manchester, United Kingdom.

Objectives: Although the Microsoft Kinect has compelling potential for gait analysis in medicine, data available to compare it with observational gait analysis (OGA) is scarce. This study compared the Microsoft Kinect and the OGA in assessing the gait parameters of apparently healthy adults. Methods: Ninety-seven apparently healthy young male adults participated in this comparative study. First, the participant’s age, height, weight, and body mass index were obtained. Afterward, gait parameters involving the number of steps, cadence, stride length, and step length were assessed concurrently following OGA standard procedures and the Microsoft Kinect during a ۶-m walk down the hallway. The obtained data were analyzed using descriptive and inferential statistics. The significance level was set at P<۰.۰۵.  Results: The Mean±SD walk time, steps, cadence, velocity, and stride length were ۸.۰۷±۱.۳۹ s, ۱۴.۰±۲.۹۶ counts, ۷۲.۹±۱۱.۹ steps/min, ۰.۸±۰.۱۳ m/s, and ۰.۷۷±۰.۱۳m, respectively. Step length was significantly higher (P<۰.۰۵) with Microsoft Kinect than OGA, whereas stride length and walk speed values were significantly (P<۰.۰۵) lower with Microsoft Kinect. A moderate but significant (P=۰.۰۰۱) positive correlation existed between Microsoft Kinect and OGA regarding walk speed. In contrast, regarding the step length, a weak but significant (P<۰.۰۵) positive correlation was found between Microsoft Kinect and OGA. Discussion: Step length values of Microsoft Kinect were significantly higher than OGA values, whereas stride length and walk speed values of Microsoft Kinect were significantly lower than OGA values. Walk speed and step length measured by Microsoft Kinect and OGA were positively correlated. Coresponding author: Saturday Nicholas Oghumu, E-mail: nicholasoghumu@unical.edu.ng You can also search for this author in:  Google Scholar

Microsoft Kinect, Observational gait analysis, Gait analysis, Gait