Remote Monitoring to Support Health Care: The designing of an application to ambulatory measure human back movements

Remote Monitoring to Support Health Care: The designing of an application to ambulatory measure human back movements

Boon, R.J.G.

Moes, C.C.M. (mentor)
Breemen, E.E.J. (mentor)
Schwietert, H.R. (mentor)

Industrial Design Engineering

Integrated Product Design

2010-06-24

This report describes the “Remote Monitoring to Support Health Care” project in which an application is designed to ambulatory measure the movements of the human back. The final design of the application called the Remote Monitoring Navale Application is part of the existing Remote Monitoring System of Evalan. Together with the other components of the system, the RMNA is capable of ambulatory monitoring the movements of the patient’s back and to provide feedback which can be used to support the health care by improving treatments. The initial target group of the Navale Application is patients who are rehabilitation after a Hernia Nuclei Pulposi surgery through treatment at a physiotherapist. This target group is a result of an explorative study to search for new opportunities for the RMS of Evalan in order to increase their market off-set. During this study the market, the medical field, the stakeholders and future aspects of a new application are research and analyzed. The first conclusion of the analysis showed that Evalan should focus on health problems which treatments can be monitored with relatively simple and cost effective sensors. The second conclusion showed that there are three interesting combinations of medical treatments and monitoring possibilities; Osteoarthritis, Dorsopathies and Multiple Sclerosis. Finally the choice has been made to focus on the Dorsopathies and especially on the HNP patients. The target group can, after the development, be expanded to patients with health problems which are caused by or are in any other way related to movements of the (lower) human back such as chronic lower back problems. This is a very interesting option because yearly 1,6 million people have this complaint and it costs approximately nine billion each year in the Netherlands. The design of the RMNA comprises of a tight fitting garment with six flexible stretch sensors which will be worn under the clothes and assesses the movements of the back by measuring the elongation of the skin caused by the movements. The garment is especially developed to transfer the elongation of the skin to the attached sensors while maintaining a high level of comfort. A significant and yet unexplored aspect of the design is the locations of the flexible stretch sensors. The optimal placement is researched by conducting multiple tests with a prototype and by reviewing results of a finite element analysis of strain patterns on the back while performing movements by Mattmann (2008). The results are that the location for a flexion movement is vertically in the centre at the height of the L3-L5 vertebrae, the location for a lateral movement is vertically at the side of the body at the height of the L2-L4 vertebrae and the location for a rotational movement is diagonally, off-centre and at the height of the L3-L4 vertebrae. At the end of the project the design of the RMNA is evaluated by testing the performance of the prototype. The performance is defined as the ability to classify movements correctly and to measure the deflection of the movement accurately. At the same time the RMNA as part of the RMS is tested by adding a prototype algorithm which can translate the measurements of the RMNA automatically in a classification and the deflection of the movement. The results of this test show that the RMNA scores almost perfectly without clothes (classification 100% and deflection 95%) and a little less with clothes on top (classification and deflection 73%). The simple prototype algorithm has an average accuracy of 80%. The results of the test also indicated areas for improvement which are translated into recommendation for further development. The first recommendation is to adjust the RMNA to perform better with clothes on top. The second recommendation is to optimize the RMNA so that other movements of the body are having less influence on the sensors. The third recommendation is to improve the reliability of the software on the M-doc and to increase the number of sensor inputs. The last recommendation is to enable the algorithm to make iterative loops to optimize the accuracy of the classification and the deflection of a movement.

design
remote monitoring
flexible stretch sensors
Hernia Nuclei Pulposi
lower back problems
smart textile
integrated sensors

http://resolver.tudelft.nl/uuid:ca3b6f8c-58bb-4a4e-a14c-106dd15f0913

Campus only

Student theses

master thesis

(c) 2010 Boon, R.J.G.