DEVELOPMENT OF A BIO SHOE SYSTEM WITH IOT FOR BIO-MEDICAL APPLICATIONS

Transcription

1 International Journal of Civil Engineering and Technology (IJCIET) Volume 8, Issue 7, July 2017, pp , Article ID: IJCIET_08_07_046 Available online at ISSN Print: and ISSN Online: IAEME Publication Scopus Indexed DEVELOPMENT OF A BIO SHOE SYSTEM WITH IOT FOR BIO-MEDICAL APPLICATIONS H Bharathi, B Annapurna, T S Arulananth and R Karthik Department of Electronics and Communication Engineering, MLR Institute of Technology, Dundigal, Hyderabad , Telangana, INDIA ABSTRACT The system was developed for remote care -taking applications which could be incorporated for patients. This system has utilized as a sensor integrated shoe and a waist belt. The foot pressures of the foot sole vital points are being measured along with the additional contribution from inertial measurement units. The measured data is being transmitted to a remote Internet of Thing (IOT) for further analysis and stored data in the (IOT) cloud would be available for future medical researchers. The system furthermore comprises activity and location tracking and fall detection system. Concerning the caretaker's convenience, an Android application has also developed. Key words: Tele-monitoring; Location Tracking; Activity Tracking; Internet of Things; Sensor Integrated Shoe; Plantar Pressure Measuring. Cite this Article H Bharathi, B Annapurna, T S Arulananth and R Karthik, Development of A Bio Shoe System with IOT For Bio-Medical Applications, International Journal of Civil Engineering and Technology, 8(7), 2017, pp INTRODUCTION As the percentage of the aging population of industrialized countries increases, so does the cost to provide health care at the hospitals. As such, there is a trend to move from a primarily centralized Health Care system to one where much of the health care is distributed and at homes, hence decreasing both budget and the burden on health care professionals such as nurses, therapists, and doctors. Tele-home-care, or telemedicine, services help physicians and medical professionals to provide clinical care services to patients remotely. There are many different uses that can be imagined from tele home-care systems such as monitoring patients with chronicle illness, tracking patients rehabilitation processes, elderly care etc Concerning on the requirements of the modern medical industry, this approach of particular interest in the search for reliable information on the evolution of different diseases such as Parkinson's disease, heart disease and diabetes that affect a large percentage of the population. Implementing real time tele-caring systems on those patients and elderly persons would be very useful to identify their conditions. Plantar pressure data have been recognized very important in the assessing such patients and information derived from plantar pressure also can editor@iaeme.com

2 Development of A Bio Shoe System with IOT For Bio-Medical Applications assist in determining the impairments in neurological disorders. Prior researches have utilized the IOT based Tele-monitoring for patients [1], [2]. This novel system implementation has addressed the gap of remotely analyzing logging plantar pressure data of patients, along with other clinically important data in real time. PLANTAR PRESSURE MEASUREMENT We measured the plantar pressure by the validated PEDARW device (Novel GmbH, Munich, Germany) This in-shoe mobile system consists in flexible and size adaptable insoles containing 99 capacitive sensors for dynamic plantar pressure measurement. An acquisition rate of 50 Hz has been used for data collecting. After a careful clinical examination of both feet, followed by an initial measurement of plantar pressure distribution during walking by PEDARW (four trials, 15 steps each), the zone of the highest plantar pressure under the left or right foot was determined by the physician. This zone was considered to be at risk for foot ulceration and was the target for off-loading during the learning session. The peak plantar pressure (PPP) at the level of the at-risk zone was measured by the Pedar-x/Expert W (Novel GmbH, Munich, Germany) software with mask option. In addition to the PPP measured under the at-risk zone to be off-loaded, we also measured the plantar pressure distribution under the whole feet in order to check if, during the at-risk zone off-loading by biofeedback, a new high pressure zone had developed under other areas of the right or left foot. For that, the PEDARW insole containing 99 sensors was divided into 11 areas (Figure 1). The PPP under the at-risk zone as well as the PPP under all other areas of both feet was measured at baseline (T0), at the end of the learning period (T1) and after the retention test at 10 days (T2). At different measurements, patients wore their own shoe. Figure 1 Division of the insole into 11 zones 2. WORKING PRINCIPLE OF PROPOSED SYSTEM Wearable device comprises a sensor integrated shoe and a waist belt. Shoe is designed to obtain force readings of each feet and transmit to the waist belt. While waist belt designed as the main controller, activity tracker, location tracker, fall detector and data transmitter to the telemonitoring platforms (Fig. 2) editor@iaeme.com

3 H Bharathi, B Annapurna, T S Arulananth and R Karthik Figure 2 Schematic diagram of overall system A. Tactile Sensor Integrated Shoe and Waist Belt Designed each shoe has a 3D printed insole (Fig. 3) which is embedded with an array of five Flexi Force piezo-resistive sensors aligned to five major foot anatomical areas based on I Walk [3] and Z. Pataki et al. [4]. Figure 3 Sensor integrated shoe Intermediate convex curved inserts made out of Silicon Rubber, inserted between Flexi Force sensor and feet to diminish the applied load. Flexi Force readings were mapped to force applied on it by using dead-weight test while a numerical simulation using COMSOL Multi physics 5.2 (Fig. 4) used to convert applied force to force on Flexi Force sensor according to results shown in Fig.5. Figure 4 Convex curved inserts (a) Positioning inserts (b) (c) Roller constraint area (d) Integral pressure probe area (e) The deformation of the hemisphere under loading editor@iaeme.com

4 Development of A Bio Shoe System with IOT For Bio-Medical Applications Experimental setup has been used to measure the overall displacement of the sensor integrated shoe and it s measured as 4mm. Prior the shoe insole layer fabrication, the shoe insole was modeled and simulated in COMSOL Multi physics 5.2 by utilizing finite element tools while measured deflection used as an input parameter to the simulation. Custom designed snob enclosure used to facilitate 3D printed layers, to reduce the slip of the sole when walking B. Activity Tracking, Fall Detection and Localizing Jay Chen et al method [5] of fall detection by means of an accelerometer is used for fall detection while basic postures are derived using both foot pressures and accelerometer data. Gait parameters such as number of strides would be counted based on the number of peaks of heel pressure sensor values. Localization of the patient is being done by GPS signals from Ublox NEO-6 GPS Module located in the waist belt at 1Hz sampling frequency combined with GSM signal triangulation for reliable operations. Due to the fact of 10Hz data acquisition frequency from each plantar force measuring sensors, the acquired data is being concatenated throughout 15 seconds as a string, then being uploaded as a lesser length encrypted string. The IOT itself does the received data decryption and further analysis. C. Tele caring Plat form The PC interface of the system and the Android application shown in Fig. 7 was implemented to meet the needs of remote tele-caring using Thing Speak IOT provided by Math Works Inc. 3. RESULTS A. Calculating Number of Steps and Walking Speed Using Walking Patterns. A walking experiment was conducted along a 35 feet long hallway by a subject of 5 feet tall male. The whole hallway was Figure 6 Positioning force sensors (a) Pressure points used by I Walk [3]. (b) Adopted vital pressure points in foot. (c) Pressure points on insole (d) Shoe insole design validation editor@iaeme.com

5 H Bharathi, B Annapurna, T S Arulananth and R Karthik Figure 7 Tele-monitoring interfaces (a) The live dash board of the IOT (b) mobile interface Traversed14 times. Equation (1) could be used to derive walking speed of the patient by using heel pressure values extracted from planter pressure data. Where stride length for a male person is taken as times Height. The average walking speed was derived as 0.44ms-1 using (1) where the actual walking speed is 0.62ms-1. Walking Speed = (Cadence * Stride Length)/60 B. Localization and Fall Detection the experiments were done within 20m radius from N and E The location is being identified and displayed as N and E The fall detection experiment was done using be a punch bag of weight 52kg (reasonably assumed to a human subject) and observed the alerting system. 4. CONCLUSION AND FUTURE WORKS This foot pressure intensity measuring approach has been implemented by tactile sensors combining with inertial measurement units to identify human postures, localizing and detect falls in real time. By incorporating a mathematical modeling and/or artificial intelligence technique along with a thorough clinical testing this system would be capable of detecting diabetic foot ulcer aggravations by foot pressure intensities, monitor both Parkinson patients and recovery of neuropaths remotely with the IOT technology based on gait abnormalities. REFERENCES [1] R. Al-Atta s, A. Yassine and S. Shirmohammadi, Tele-Medical Applications in Home- Based Health Care, 2012 IEEE International Conference on Multimedia and Expo Workshops, [2] J. Gomez, B. Oviedo and E. Zhuma, Patient Monitoring System Based on Internet of Things, Procedia Computer Science, Vol. 83, pp , [3] I Walk: An Intelligent Active Knee Exoskeleton Jiahe Liao, Jiahe works, [Online]. Available: [Accessed: 11- Aug- 2016]. [4] Z. Pataky, L. Faravel, J. Da Silva and J. Assal, A new ambulatory foot pressure device for patients with sensory impairment. A system for continuous measurement of plantar pressure and a feed-back alarm, Journal of Biomechanics, Volume 33 Number 9, pp , [5] P. Dayaker, Y. Madan Reddy and M Bhargav Kumar, A Survey on Applications and Security Issues of Internet of Things (IoT), International Journal of Mechanical Engineering and Technology, 8(6), 2017, pp editor@iaeme.com

6 Development of A Bio Shoe System with IOT For Bio-Medical Applications [6] Snehal R. Shinde, A. H. Karode and Dr. S. R. Suralkar, Review on IOT Based Environment Monitoring System, International Journal of Electronics and Communication Engineering and Technology, 8(2), 2017, pp [7] Hariharr C Punjabi, Sanket Agarwal, Vivek Khithani, Venkatesh Muddaliar and Mrugendra Vasmatkar, Smart Farming Using IoT, International Journal of Electronics and Communication Engineering and Technology, 8(1), 2017, pp [8] J. Chen, K. Kwong, D. Chang, J. Luk and R. Bajcsy, Wearable Sensors for Reliable Fall Detection, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, editor@iaeme.com