International Journal of Computer Networking, Wireless and Mobile Communications (IJCNWMC) ISSN(P): 2250-1568; ISSN(E): 2278-9448 Vol. 4, Issue 3, Jun 2014, 1-6 © TJPRC Pvt. Ltd.

ANALYSIS OF HUMAN LIMBS MOTION BY DESIGNING WEARABLE WIRELESS DEVICE MESSAGE ALERT SYSTEM FOR VARIOUS APPLICATIONS

PRASAD K. BHASME 1 & UMESH W. HORE 2 1M.E Student, Department of Electronics and Telecommunication, PRPCET, Amravati, Maharashtra, India 2Professor, Department of Electronics & Telecommunication Engineering, PRPCET, Amravati, Maharashtra, India

ABSTRACT

Motion sensing has played an important role inthe study of human biomechanics as well as the entertainment industry. Although existing technologies, such as optical orinertial based systems, have relatively high accuracy in detecting body motions, they still have inherentlimitations with regards to mobility and wearability. Most of the existing systems need wiring that commands the natural movement. In this project, to overcome this flaw, a wearable wireless sensor network with message status using accelerometers and flex sensor will be about to be designed in this undertaking. The wireless feature enables the uncontrolled movement of the human body as obstruct to a wired monitoring device & makes the system truly movable. Patient monitoring systems are gaining their importance as the fast-growing global elderly population increases demands for caretaking. These systems use wireless technologies to transmit vital signs for medical evaluation.Tracking of human motion has attracted significant interest in recent years due to its wide ranging applications such as rehabilitation, , sports science, medical science and surveillance. In our project we will introduce the FLEX sensors, MEM sensors & GSM Technology.

KEYWORDS: Flex Sensors, MEMS, GSM, Microcontroller

INTRODUCTION

As health awareness increases in society and technology continues to push its boundaries, there is an increasing demand for medical devices that provide around the clock assessment of a subject’s general well-being. These self-monitoring devices have the potential to dramatically improve a person’s health and productivity; thus improving the individual’s quality of life. Modern people have to deal with the fast-paced learning, work and life, facing more and more competition and challenges, and people with chronic illnesses such as heart disease become more and more. The ever-increasing rise in the number of chronically ill people is a growing burden on healthcare institutions. So in this disease, it is necessary to monitor Human Limb Motion along with Muscle temperature and heart rhythm. To achieve this mentioned, we are using this project to implement all that which helps in better and fast recovery of the patient.

In recent years, magnetic &inertial tracking has fascinated much interest as they are the source-free approaches unlike the radar & audio that requires an emission source. The development of flex sensor technology & microelectro mechanical system technology had also made such sensors cheaper, lighter & smaller. In this project the FLEX sensors &MEMS sensors will be introduced into the application of medical & sports. The wireless feature activates the unrestrained movement of the human body as a counter to a wired monitoring device & makes the system truly movable.

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Micro-Electro-Mechanical Systems, or MEMS, is a technology that in its most general form can be defined as miniaturized mechanical and electro-mechanical elements (i.e., devices and structures) that are made using the techniques of micro fabrication. The critical physical dimensions of MEMS devices can vary from well below one micron on the lower end of the dimensional spectrum, all the way to several millimeters.Likewise, the types of MEMS devices can vary from relatively simple structures having no moving elements, to extremely complex electromechanical systems with multiple moving elements under the control of integrated microelectronics.

The small form factor and light weight feature of the sensor nodes also allow easy attachment to the limbs.

Figure 1: Block Diagram

Also, our project will be applicable to lots of other areas

Figure 2: Functional Block Diagram

RELATED WORK

Yuan Luo; Hongmei Yang; Zhangfang Hu suggests their thoughts for Human limb motion real-time tracking based on Cam Shift for intelligent rehabilitation system and stated that the Intelligent rehabilitation system has become a hot topic. Considering the limb motion and selected color probability distribution all together, we put forwards the modified algorithm, which enhances anti-interference ability and avoids distracting. In conclusion, based on the Open CV library, use Cam Shift tracking algorithm to achieve limb motion tracking [IEEE International Conference on vol., no., pp. 343, 348, 19-23 Dec. 2009].[1]

Fitzgerald et al also maintains information for the development of a wearable motion capture suit & virtual reality biofeedback system for the instruction & analysis of sports rehabilitation exercises & advised that the development

Impact Factor (JCC): 5.3963 Index Copernicus Value (ICV): 3.0 Analysis of Human Limbs Motion by Designing Wearable Wireless Device Message Alert System for Various Applications 3

& design of a computer game for directing an athlete through a series of prescribed rehabilitation exercises. To care for the musculoskeletal type injuries along with trying to improve athletes & physical performance are prescribed exercise programmed by trained specialists. They described that illustrates how a clinician can at a later date review the athletes progress & subsequently alter the exercise programmed as they see fit [29th Annual International Conference of the IEEE, vol., no., pp. 4870,4874, 22-26 Aug. 2007]. [2]

TRENDS IN OUR PROJECT

This chapter gives the information of the trends in the sensor technology and the technology used in the project i.e. the flex sensor technology and gesture based technology.

Sensor Technology

Sensors allow detection, analysis, and recording of physical phenomenon that are difficult to otherwise measure by converting the phenomenon into a more convenient signal. Sensors convert physical measurements such as displacement, velocity, acceleration, force, pressure, chemical concentration, or flow into electrical signals. A revolution in micro fabricated sensors occurred with the application of semiconductor fabrication technology to sensor construction. By etching and depositing electrically conductive and nonconductive layers on silicon wafers, the sensor is created with the electrical sensing elements already built into the sensor. The products created using these techniques are called micro electro mechanical systems, or MEMS.

The entire MEMS sensor is fabricated on a small section of a single silicon wafer or a stack of wafers bonded together. Reducing the area of the sensor layout both decreases the area of the sensor and increases the number of sensors produced on each wafer. The silicon dies are then packaged in chip carriers for use. Many types of inertial sensors have been fabricated as MEMS. The original MEMS sensors were pressure sensors using piezo resistive sensing elements, 2 while current MEMS sensors include accelerometers (measuring either linear 3 or angular4 acceleration), shear stress sensors, 5 chemical concentration sensors, 6 and gyroscopes. 7 This project uses single-axis MEMS linear accelerometer sensors fabricated at MIT to create a three-dimensional accelerometer sensor system suitable for measuring the acceleration of human hand motion.

The focus of this project is measuring involuntary hand motion in people who have a significant hand tremor. Human hand motion can be broadly divided into two categories: voluntary and involuntary. Voluntary motion is intentional, such as throwing a baseball or changing the TV channel using a . Involuntary motion is unintentional movement. One example of involuntary hand motion is the small vibrations in a person’s hand when they are trying to keep their hand still, due to small imperfections in the human body’s biomechanical feedback mechanisms. In healthy people this involuntary hand motion is small but measurable.

Technology Used Flex Sensor Technology The Flex Sensor patented technology is based on resistive carbon elements. As a variable printed resistor, the Flex Sensor achieves great form-factor on a thin flexible substrate. When the substrate is bent, the sensor produces a resistance output correlated to the bend radius-the smaller the radius, the higher the resistance value.

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Various sensor technologies are used to capture physical data such as bending of fingers. Often a motion tracker, such as a magnetictracking device or inertial tracking device, is attached to capture the global position/rotation data of the glove. These movements are then interpreted by the software that accompanies the glove, so any one movement can mean any number of things. Gestures can then be categorized into useful information, such as to recognize Sign Language or other symbolic functions. Expensive high-end wired gloves can also provide hectic feedback, which is a simulation of the sense of touch. This allows a wired glove to also be used as an output device. Traditionally, wired gloves have only been available at a huge cost, with the finger bend sensors and the tracking device having to be bought separately.

Gesture Based Technology

Gesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms. Gestures can originate from any bodily motion or state but commonly originate from the face or hand. Current focuses in the field include emotion recognition from the face and hand . Many approaches have been made using cameras and computer vision algorithms to interpret sign language. However, the identification and recognition of posture, gait and human behaviors is also the subject of gesture recognition techniques. Gesture recognition can be seen as a way for computers to begin to understand human body language, thus building a richer bridge between machines and humans.

HARDWARE USED Microcontroller ATMEGA128

The Atmel® AVR® core combines a rich instruction set with 32 general purpose working registers. All the 32 registers are directly connected to the Arithmetic Logic Unit (ALU), allowing two independent registers to be accessed in one single instruction executed in one clock cycle. The resulting architecture is more code efficient while achieving throughputs up to ten times faster than conventional CISC microcontrollers. The ATmega128 device is supported with a full suite of program and system development tools including: C compilers, macro assemblers, program debugger simulators, in-circuit emulators, and evaluation kits. The device is manufactured using Atmel’s high-density nonvolatile memory technology. The On chip Flash allows the program memory to be reprogrammed in-system through an SPI serial interface, by a conventional nonvolatile memory programmer, or by an On-chip Boot program running on the AVR core. The boot program can use any interface to download the application program in the application Flash memory. Software in the Boot Flash section will continue to run while the Application Flash section is updated, providing true Read-While-Write operation. By combining an 8-bit RISC CPU with In-System Self-Programmable Flash on a monolithic chip, the Atmel ATmega128 is a powerful microcontroller that provides a highly flexible and cost effective solution to many embedded control applications.

Accelerometer ADXL335

The ADXL335 is a small, thin, low power, complete 3-axis accelerometer with signal conditioned voltage outputs. The product measures acceleration with a minimum full-scale range of ±3 g. It can measure the static acceleration of gravity in tilt-sensing applications, as well as dynamic acceleration resulting from motion, shock, or vibration. The user selects the bandwidth of the accelerometer using the CX, CY, and CZ capacitors at the XOUT, YOUT, and ZOUT pins. Bandwidths can be selected to suit the application, with a range of 0.5 Hz to 1600 Hz for the X and Y axes, and a range of 0.5 Hz to 550 Hz for the Z axis.

Impact Factor (JCC): 5.3963 Index Copernicus Value (ICV): 3.0 Analysis of Human Limbs Motion by Designing Wearable Wireless Device Message Alert System for Various Applications 5

Wireless Serial Communication RF Modem

RF modem can be used for applications that need two way wireless data transmission. It features adjustable data rate and reliable transmission distance. The communication protocol is self-controlled and completely transparent to user interface. The module can be embedded to your current design so that wireless communication can be set up easily.

CONCLUSIONS

An uncontrolled & ambulatory measurement system based on a wearable wireless sensor network for searching the human arm motion in the sagittal plane has been proposed. The wireless feature activates the uncontrolled movement of the human body as repelled to a wired monitoring device & makes the system purely movable.This allows the system to arrange in a cluttered home environment. The light weight feature small form factor of the sensor nodes also permits easy attachment to the limbs. To compare with other existing appeals, the new system is movable & easy to use. It permits the patients to be monitored without rehabilitation & controlled can be taking place in a home environment rather than laboratory in the hospital. There will be no chance of signal jamming by other nodes.

REFERENCES

1. Yuan Luo; Hongmei Yang; Zhangfang Hu, "Human limb motion real-time tracking based on CamShift for intelligent rehabilitation system," Robotics and Biomimetics (ROBIO), 2009 IEEE International Conference on , vol., no., pp. 343, 348, 19-23 Dec. 2009

2. Fitzgerald, D.; Foody, J.; Kelly, D.; Ward, T.; Markham, C.; McDonald, J.; Caulfield, B., "Development of a wearable motion capture suit and virtual reality biofeedback system for the instruction and analysis of sports rehabilitation exercises," Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE , vol., no., pp. 4870, 4874, 22-26 Aug. 2007

3. GuoXiong Lee; Kay Soon Low; Taher, T., "Unrestrained Measurement of Arm Motion Based on a Wearable Wireless Sensor Network," Instrumentation and Measurement, IEEE Transactions on , Vol. 59, no. 5, pp. 1309, 1317, May 2010

4. D. Jack, R. Boian, A. S. Merians, M. Tremaine, G. C. Burdea, S. V. Adamovich, M. Recce, and H. Poizner, ―Virtual reality-enhanced stroke rehabilitation, IEEE Trans. Neural Syst. Rehabil. Eng. , vol. 9, no. 3, pp. 308–318, Sep. 2001.

5. J.M. Zheng, K.W. Chan, and I. Gibson, ―Virtual reality, IEEE Potentials , vol. 17, no. 2, pp. 20–23, Apr. 1998.

6. Chaczko, Z.; Kale, A.; Chiu, C., "Intelligent health care — A Motion Analysis system for health practitioners," Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2010 Sixth International Conference on , vol., no., pp. 303,308, 7-10 Dec. 2010

7. HouHonglun, HuoMeimei, Wu Minghui, “sensor-based wireless wearable systems for healthcare and falls monitoring” International journal on smart sensing and intelligentsystems vol. 6, no. 5, December 2013

8. Pankil M. Butala, Yuting Zhang, Thomas D. C. Little, Robert C. Wagenaar, “Wireless System for Monitoring and Real-Time Classification of Functional Activity” IEEE 978-1-4673-0298-2/12/$31.00 ©2012

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