Development of a System for Anatomical Landmarks Localization using Ultrasonic Signals

review of the current protocols and techniques for the anthropometric measurements and postural assessment for wheelchair users and individuals with severe musculoskeletal problems was given. It was concluded that both contact and non contact methods have a number of significant limitations including time consuming measurement procedure, high cost and risk of excessive exposure to radiation. Many current approaches do not enable clinicians to accurately record and analyze the patient’s musculoskeletal configuration. The challenge still remains to combine the body shape data with the precise identification and localization of anatomical landmarks for postural assessment. To address the need for easy to use, low cost, reliable measurement of anatomical landmarks ultrasound measurement system has been proposed. The main elements of the system are: ultrasound transmitters, receiver, digital-analog converter, signal conditioning equipment and laptop executing the signal processing algorithm. The prototype of the system was build and tested. The preliminary measurements of ultrasonic signals were realized and demonstrated the potential for this technique to be used in anthropometric and postural assessments in the future.“© © 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Rule-based algorithm for the classification of sitting postures in the sagittal plane from the Cardiff Body Match measurement system

The purpose of this paper is to present the design and implementation of a novel rule-based algorithm for the classification of sitting postures in the sagittal plane. The research focused on individuals with severe musculoskeletal problems and, thus, specific requirements for posture and pressure management. Clients' body shapes were captured using the Cardiff Body Match system developed by the Rehabilitation Engineering Unit, Cardiff and Vale University Health Board. The algorithm consists of four main steps: the first step is the symmetry line detection, the second step involves the mathematical analysis of the curvature of the backrest profile, the third step is the sitting posture classification and the fourth step is the extraction of the geometric parameters from the curve. The results show the classification system was successful in identifying four types of curves characterizing sitting postures using local derivatives as curve descriptors with an overall accuracy of 93.9%.