Feasibility Study of Using Microsoft Kinect for Physical Therapy Monitoring

Feasibility Study of Using Microsoft Kinect for Physical Therapy Monitoring

Wenbing Zhao, Deborah Espy, Ann Reinthal, Hai Feng
Copyright: © 2015 |Pages: 13
DOI: 10.4018/978-1-4666-5888-2.ch547
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Introduction

In preventive and rehabilitative health care, physical exercise is a powerful intervention. However, many people do not adhere to the prescribed program (Bassett, 2003) which may require in the range of thousands of practice repetitions (Kleim and Jones, 2008). Also, exercises may be performed incorrectly, making the exercise ineffective, or even dangerous (Escamilla et al., 2009; Tino & Hillis, 2010). Exercise programs prescribed to address specific problems, and even many preventative wellness programs for healthy older adults, must be individually tailored by a clinician due to the presence of co-morbidities and additional impairments. The current state-of-the-art for exercise instruction and monitoring is usually limited to written instructions, exercise recording logs, and simple repetition counting devices. Unfortunately, this practice has a number of problems:

  • The patient does not receive any feedback on the quality of the prescribed exercises.

  • The clinician has no way of knowing whether or not the patient has carried out the prescribed exercises correctly and with the required number of repetitions.

Correct adherence to supplemental home exercise is essential for safe, effective, and efficient care. The lack of correct feedback during independent in-home exercise is therefore a serious concern. The use of simple counting devices helps verify the exercise repetitions. However, such simple, commercially available devices cannot fully capture all the required movements beyond the most simple, such as counting steps or recording overall amounts of activity (Wagner et al., 2012; Yang & Hsu, 2010), and are, therefore not useful for most prescribed home exercises.

The release of the Microsoft Kinect sensor, which is equipped with a depth camera capable of measuring 3 dimensional positions of the objects in its view, has triggered tremendous interest in its use to monitor in-home physical therapy exercises (Chang et al., 2013; Chang et al., 2012; Garcia et al., 2012; Gibson et al., 2012; Guerrero & Uribe-Quevedo, 2012; Huang, 2011; Zannatha et al., 2013; Pastor et al., 2012). This is not surprising because:

  • The Kinect sensor can be programmed to provide continuous feedback about correct exercise performance to the patient exercising at home, as it simultaneously records the session for review by the therapist.

  • Kinect is an inexpensive device. The first generation of Kinect sensor is available commercially for around $100, which is about the cost of a single physical therapy session.

Hence, a Kinect-based system could facilitate proper performance of the exercise or fitness program, increase patient accountability, allow the clinician to correct any errors in exercise performance, and allow program modification or advancement as needed. Hence, the Kinect sensor based system could potentially provide sufficient feedback and guidance to patients performing clinician prescribed in-home exercises, significantly minimizing costly and inconvenient trips to outpatient centers, and improving the effectiveness and outcomes of courses of treatment.

Key Terms in this Chapter

Natural User Interface: A natural user interface enables users to interact with a computer or game console via gestures and voice commands instead of keyboard, mouse, or game controller.

Sagittal: Plane: Using a three-dimensional (x-y-z) coordinate system, this is the plane dividing the left and right sides of the body; movement in the sagittal plane is typical viewed from a lateral perspective; an example of movement in this plane is shoulder flexion where the upper extremity is moved from the side to up in front of the body.

Microsoft Kinect: A sensor produced by Microsoft that is equipped with a Webcam, a depth camera, and a microphone arrays. It is designed to facilitate a natural user interface.

Frontal Plane: Using a three-dimensional (x-y-z) coordinate system, this is the plane dividing the front and back half of the body; movement in the frontal plane is typical viewed from an anterior or posterior perspective; an example of movement in this plane is hip abduction where the lower extremity is moved out to the side of the body from the midline.

Occlusion: An occlusion occurs when a joint or more is hidden from the camera. Self-occlusion means that one body part hides another part.

Floor Clipping Plane: As part of the Microsoft Kinect SDK, each skeleton frame contains a set of parameters that can be used to determine the floor plane as seen by the Kinect sensor.

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