title: Accurate upper body rehabilitation system using kinect.
abstract: The growing importance of Kinect as a tool for clinical assessment and rehabilitation is due to its portability, low cost and markerless system for human motion capture. However, the accuracy of Kinect in measuring three-dimensional body joint center locations often fails to meet clinical standards of accuracy when compared to marker-based motion capture systems such as Vicon. The length of the body segment connecting any two joints, measured as the distance between three-dimensional Kinect skeleton joint coordinates, has been observed to vary with time. The orientation of the line connecting adjoining Kinect skeletal coordinates has also been seen to differ from the actual orientation of the physical body segment. Hence we have proposed an optimization method that utilizes Kinect Depth and RGB information to search for the joint center location that satisfies constraints on body segment length and as well as orientation. An experimental study have been carried out on ten healthy participants performing upper body range of motion exercises. The results report 72% reduction in body segment length variance and 2° improvement in Range of Motion (ROM) angle hence enabling to more accurate measurements for upper limb exercises.
authors.forename: Sanjana
authors.initials: S
authors.lastname: Sinha
authors.forename: Brojeshwar
authors.initials: B
authors.lastname: Bhowmick
authors.forename: Kingshuk
authors.initials: K
authors.lastname: Chakravarty
authors.forename: Aniruddha
authors.initials: A
authors.lastname: Sinha
authors.forename: Abhijit
authors.initials: A
authors.lastname: Das
mesh_terms: D000328:Adult; D004551:Elbow Joint / Q000502:physiology; D005542:Forearm / Q000033:anatomy & histology; D006801:Humans; D008875:Middle Aged; D016059:Range of Motion, Articular; D000071939:Stroke Rehabilitation / Q000295:instrumentation*; D014955:Wrist Joint / Q000033:anatomy & histology; D055815:Young Adult