Applied Mechanics and Materials Vol 772 (2015) pp 597-602 © (2015) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.772.597
Submitted: 2015-02-10 Revised: 2015-02-12 Accepted: 2015-02-25
Design of a Scoliosis Monitoring System using Inertial Sensors VOINEA Gheorghe Daniel, 1,aand BUTNARIU Silviu 2,b 1,2
Transilvania University of Brasov, 29 Eroilor Blvd., RO-500036, Brasov, Romania a
[email protected],
[email protected]
Keywords: scoliosis, inertial sensors, motion tracking, Kalman.
Abstract. This paper presents the design of an innovative system for the diagnosis and treatment of spine disorders, in particular, the scoliosis. The product consists in a mechatronic device that is able to measure inreal time the instantaneous position of the human spine, facilitating a precise diagnosis as well as continuous monitoring for prevention and/or treatment of spine disorders. Introduction Spinal motion measurement has a key role in the rehabilitation process of patients with spinal deviations. One of these disorders is scoliosis which consists of a lateral curvature of the spine, where the Cobb angle exceeds 10, as specified by the Scoliosis Research Society[1]. The standard method for diagnosing scoliosis is with 2D anterior-posterior, full length spine radiographs[2]. Patients with a Cobb angle of less than 25(mild scoliosis) are recommended physical therapyand regular observation to monitor the progression or regression. Analysis of existing equipment A method for measuring spinal curvature is by using potentiometric goniometers. This device has a number of precision potentiometers that are connected by a series of metal bars for the acquisition of coordinates in three-dimensional space. The potentiometric goniometers are used with success in clinical and research applications, but they are not appropriate for long term monitoring because of the time needed to fit and align the system, the size of it and the high costs. Advances in the telecommunications and electronics have enabled more precise and reliable motion capture system. Of large interest are the human motion tracking systems used in rehabilitation therapies [3, 4] and remote monitoring networks for patients in hospitals and also in their own homes [5]. Health monitoring involves the integration of research from domains such as data acquisition, sensors, data storage and communication, signal processing, feature extraction techniques and multi-sensor data fusion. Data fusion is the synergistic use of data and knowledge from multiple resources in order to create a consistent and accurate representation of a system. There are several motion capture technologies that have been developed in recent years, such as optical, image-based, mechanical, magnetic, acoustic and hybrid systems. Optical motion capture systems are commonly used in the computer animation community, in the film industry and medical diagnosis and rehabilitation [6, 7]. This approach offers reliable and accurate results, but comes with poor portability and is very expensive. These systems are based on a large number of cameras using triangulation methods and markers that are placed on the body, therefore, they can be used successfully only in controlled environments[8]. Using computer vision techniques to obtain motion parameters from video footage is less accurate than optical systems, but this approach does not require the use of special markers[9]. Acoustic systems use transceivers to measure the time of flight of an audio signal in order to compute the marker locations. A major drawback is the limited number of markers and a high sensitivity to external magnetic fields[10]. Inertial measurement units (IMUs) have become the most used devices in the study of human movement because they are small, wearable and non-invasive. An IMU is an electronic device that measures and transmits velocity, orientation and gravitational forces, using a combination of accelerometers, gyroscopes and also magnetometers. All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of Trans Tech Publications, www.ttp.net. (ID: 79.114.197.139-24/04/15,06:40:43)
598
Advanced Research in Aerospace, Robotics, Manufacturing Systems, Mechanical Engineering and Bioengineering
Proposed methodology In order to achieve a mobile devicewhich is ableto measurethe spinal posture,we consider the use of inertial sensors mounted on the back of the patient (Fig. 1).
Fig. 1 Method of measuring the position of the spine Devices that can monitor and transmit data continuously would allow telecare systems to accommodate many more pathologies for which intermittent monitoring is not sufficient. Healthcare providers would then be able to increase the quality of life for their patients. The proposed system can be divided into two separate components: calibrating the deviceand treatmentimplementation.In order to calibrate the system, several steps are required: 1. Measurement of anthropometrical data by a physician, using special equipment; 2. Build a generic CAD model; 3. Identify spine curvature, as presented in Fig.2, give a diagnostic and recommend a certain posture to keep; 4. Transmit the data to the device. Once the custom equipment is calibrated, as presented in Fig. 3, the patient can begin the rehabilitation process. The scoliosis monitoring system has two options to interact with the patient: With a buzzer, which is attached to an inertial sensor. Fig.2 The four sensors and When the patient has a bad posture for a predetermined their reference systems (a) period of time, he will receive a gentle vibration to remind and the corresponding him to straighten up; polyline (b) Through the smartphone application. The patient can view the recommended posture and/or their current posture in real time.
Fig. 3 Configuring a scoliosis monitoring system
