IEEE 2017-2018 Project Titles on Bio Medical

Abstract:

Utilizing the body surface as the signal transmission medium, capacitive coupling human body communication (CC-HBC) can achieve a much higher energy efficiency than conventional wireless communications in future wireless body area network (WBAN) applications. Under the CC-HBC scheme, the body surface serves as the forward signal path, whereas the backward path is formed by the capacitive coupling between the ground electrodes (GEs) of transmitter (TX) and receiver (RX). So the type of communication benefits from a low forward loss, while the backward loss depending on the GE coupling strength dominates the total transmission loss. However, none of the previous works have shown a complete research on the effects of GEs. In this paper, all kinds of GE effects on CC-HBC are investigated by both finite element method (FEM) analysis and human body measurement. We set the TX GE and RX GE at different heights, separation distances, and dimensions to study the corresponding influence on the overall signal transmission path loss. In addition, we also investigate the effects of GEs with different shapes and different TX-to-RX relative angles. Based on all the investigations, an analytical model is derived to evaluate the GE related variations of channel loss in CC-HBC.

Abstract:

In this paper, a communication system has been proposed which converts sign language used by dumb people into speech. It is done based on the novel hand gesture recognition technique. This solution approach consists of a hardware module and software application. In hardware module - The Gesture recognition is done with the help of sensor glove which consists of 5 accelerometer sensors, a microcontroller and Bluetooth chip which are best positioned in fingers, based on the analysis of American Sign Language (ASL) signs. The design of glove and the concept of decoding gestures by considering the axis orientation with respect to gravity and their corresponding voltage levels are discussed. In Software part - an android application named Speaking gestures have been developed. It receives the data (alphabet/word) via Bluetooth, converts them into text and speaks it out. The entire process of speech synthesis has been tested and the test results displaying the alphabets and words have been shown.

Abstract:

Each and every person in this world has a desire to live a normal human life but accidents, diseases, elder-ship make their desire into disability. Moreover, there are lots of handicaps and elders as well as the number of paralyzed people are increasing day by day. They always need another person in moving and have to go under some physical therapies under the guidance of a therapist to recuperate their strain back. In this paper the proposed system helps them to move freely & safely and also takes the activities of a therapist in a cost effective manner. This system is a combination of different controlling features, has the ability to detect obstacle and provides few kinds of therapies. A smart wheelchair is developed by using voice recognition system to control the movement of wheelchair and also with Arduino interfaced joystick. Besides, an ultrasound system provides the facility of automatic obstacle detection. The aim of research is to compact many facilities in a single wheelchair at low cost.

Abstract:

This study proposes a myoelectric Human Machine Interface (HMI) to control a 6-DOF robotic manipulator with a 1-DOF gripper. Previous study has shown that using dynamic gestures such as “snapping fingers” is more reliable in the limb position changes than using static gestures such as “closed hand”. This work utilizes dynamic gestures and additionally infers muscle forces from the EMG signals to activate/inactivate a myoelectric HMI system. In order to estimate the performance of the myoelectric interface, real-time classification accuracy, path efficiency, and time-related measures are introduced. For comparison purposes, the performance of a GUI button-based jog interface was also measured. The average real-time classification accuracy of the myoelectric interface is approximately 95%. The path efficiency of the myoelectric interface also appears to be similar to that of the jog interface reflecting the utility of this approach for HMI applications in robotics.

Abstract:

Falls can result in physical and psychological trauma, especially for the elderly. In order to improve the quality of life of these patients this work presents the development of a fall detection and body positioning with a heart rate monitoring system. This system consists of the sensing equipment, gateway and a real-time patient monitoring structure. The sensing device obtains information from accelerometers and gyroscope and sends them to the gateway via ZigBee technology, which makes the processing of the data and sends them to the cloud. The current patient body position and temperature sensing are provided through a web platform and Android application. The body, walking and falls position were respectively satisfactory in 100%, 90% and 60% of cases during tests at the laboratory. We conclude that our current proposal achieved the goal of patient fall detection with a corporal temperature monitoring using a low cost budget implementation.

Abstract:

In this paper, we present an unobtrusive cuffless blood pressure (BP) monitoring system based on pulse arrival time (PAT) for facilitating long-term home BP monitoring. The proposed system consists of an electrocardiograph (ECG), a photoplethysmograph (PPG), and a control circuit with a Bluetooth module, all of which are mounted on a common armchair to measure ECG and PPG signals from users while sitting on the armchair in order to calculate continuous PAT. Considering the good linear correlation of systolic BP (SBP) and the nonlinear correlation of diastolic BP (DBP) with PAT, a new BP estimation method was proposed. Ten subjects underwent BP monitoring experiments involving stationary sitting on a chair, lying on a bed, and pedaling using an ergometer in order to assess the accuracy of the estimated BP. A cuff-type BP monitor was used as reference in the experiments. Results showed that the mean difference of the estimated SBP and DBP was within 0.2 ± 5.8 mmHg (p <; 0.00001) and 0.4 ± 5.7 mmHg (p <; 0.00001), respectively, and the mean absolute difference of the estimated SBP and DBP were 4.4 and 4.6 mmHg, respectively, compared to references. Additionally, five subjects participated in data collections consisting of sitting on a chair twice a day for one month. Compared to the reference, the difference did not obviously increase along with time, even though individualized calibration was executed only once at the beginning. These results suggest that the proposed system has quite the potential for long-term home BP monitoring.

Abstract:

The main focus of the paper is to address an e-health acquisition, transmission and monitoring system. Patient health parameters are monitored by wireless sensor network and communicated to the far end through Zigbee interface. Data received at far end is monitored by MATLAB. If the parameters are abnormal it configures the GSM module to send SMS on doctor mobile phone. System implemented in this paper is made for such patients who are not in the critical state but they need to be monitored continuously. When the critical condition occurs, system will originate an alarming message and send it to the doctor. It is fast, less costly and monitors patient remotely from their homes.

Abstract:

Healthcare industry has perpetually been on the forefront in the adoption and utilization of information and communication technologies (ICT) for the efficient healthcare administration and treatment. Recent developments in ICT and the emergence of Internet of Things (IoT) have opened up new avenues for research and exploration in the all fields including medical and healthcare industry. Hospitals have started using the cell instruments for communication intent and for this intent internet of things (IoT) has been used and fused with wi-fi sensor node reminiscent of RFID, NFC tag and small sensor nodes. The usage of a cellular agent in healthcare procedure underneath wi-fi community environment gives a chance to explore improved services for patients and staffs reminiscent of medical professionals and nurses given that of its mobility. In this paper novel method to utilize it IoT within the field of scientific and crafty wellness care are presented. The majority of the survey exist about the different healthcare approaches used in the IoT, similar to, wireless well-being monitoring, U-healthcare, E-healthcare, Age-friendly healthcare techniques. This paper describes and proposes a complete monitoring existence cycle and effective healthcare monitoring system designed by using the IoT and RFID tags. The experimental results in this paper show the robust output against various medical emergencies. In this system to get the veracious evaluation results, supervising and weighing the health status of patient and to increase the power of IoT, the combination of microcontroller with sensors is presented.

Abstract:

Fall detection for elderly and patient is a very important service that has the potential of increasing autonomy of elders while minimizing the risks of living alone. It has been an active research topic due to the fact that health care industry has a big demand for products and technology of fall detection systems. Owing to the recent rapid advancement in sensing and wireless communication technologies, fall detection systems have become possible. They allow detecting fall events for the elderly, monitoring them, and consequently providing necessary help whenever needed. This paper describes the ongoing work of detecting falls in independent living senior apartments using force sensors and three-axis accelerometers concealed under intelligent tiles. The force sensors permit detecting elders' falls, locating, tracking, and recognizing human activities (walking, standing, sitting, lying down, falling, and the transitions between them). However, the detection accuracy on real data contains false alarms coming from falling and lying postures. To solve this issue, we propose the fusion between the force sensor measurements and the accelerometer sensor decisions. As a consequence, the system accuracy is satisfactory, and the results show that the proposed methods are efficient, and they can be easily used in a real elder tracking and fall detection system.

Abstract:

Wearable health sensors are about to change our health system. While several technological improvements have been presented to enhance performance and energy-efficiency, battery runtime is still a critical concern for practical use of wearable biomedical sensor systems. The runtime limitation is directly related to the battery size, which is another concern regarding practicality and customer acceptance. We introduced ULPSEK—Ultra-Low-Power Sensor Evaluation Kit— for evaluation of biomedical sensors and monitoring applications (http://ulpsek.com). ULPSEK includes a multiparameter sensor measuring and processing electrocardiogram (ECG), respiration, motion, body temperature, and photoplethysmography (PPG). Instead of a battery, ULPSEK is powered using an efficient body heat harvester. The harvester produced 171 μW on average, which was sufficient to power the sensor below 25º C ambient temperature. We present design issues regarding the power supply and the power distribution network of the ULPSEK sensor platform. Due to the security aspect of self-powered health sensors, we suggest a hybrid solution consisting of a battery charged by a harvester.

Abstract:

Monitoring heart diseases often requires frequent measurements of electrocardiogram (ECG) signals at different periods of the day, and at different situations (e.g., traveling, and exercising). This can only be implemented using mobile devices in order to cope with mobility of patients under monitoring, thus supporting continuous monitoring practices. However, these devices are energy-aware, have limited computing resources (e.g., CPU speed and memory), and might lose network connectivity, which makes it very challenging to maintain a continuity of the monitoring episode. In this paper, we propose a mobile monitoring solution to cope with these challenges by compromising on the fly resources availability, battery level, and network intermittence. In order to solve this problem, first we divide the whole process into several subtasks such that each subtask can be executed sequentially either in the server or in the mobile or in parallel in both devices. Then, we developed a mathematical model that considers all the constraints and finds a dynamic programing solution to obtain the best execution path (i.e., which substep should be done where). The solution guarantees an optimum execution time, while considering device battery availability, execution and transmission time, and network availability. We conducted a series of experiments to evaluate our proposed approach using some key monitoring tasks starting from preprocessing to classification and prediction. The results we have obtained proved that our approach gives the best (lowest) running time for any combination of factors including processing speed, input size, and network bandwidth. Compared to several greedy but nonoptimal solutions, the execution time of our approach was at least 10 times faster and consumed 90% less energy.

Abstract:

Liquid supply risk management done for inpatient care of the elderly or persons suffering from diseases is currently a time intensive procedure. The paper describes the design and evaluation of an automatic beverage monitoring system. An electronic device is presented, which is able to measure the fluid intake of the patient and provide an automated documentation and connection to existing software architecture. In a user-oriented study the functionality and acceptance were evaluated and the results show that drinking motivation can verifiably result in temporarily increased hydration.

Abstract:

In the ageing society, medical service has changed from the “cure-service” for patients to the “care-service” for semi-healthy or healthy people. The care service for healthy people in daily-life requires using a homecare kit to measure and analyze their personal bio-signal in daily activities. The acquisition signal in daily-life can help detect early symptoms of disease and enable their cure. In this paper, we propose a homecare kit based cloud platform for the acquisition, analysis and management of the multiple bio-signals from daily-life activity, and for sending alerts to another user (guardian) or doctor when a dangerous situation occurs. In the proposed platform, the homecare kit consists of wearable devices with embedded biosensors: ACC, PPG/SpO2, Breathing, ECG, and the user can easily wear and use the homecare kit for measuring the bio-signal in daily life or while sleeping. If the user is a patient with a disease such as arrhythmias, during a dangerous situation such as breaking down or a stop in breathing, the alert messaging service can alert the asynchronous push message to the registered guardian or doctor. In the hospital, healthcare professional staff can also analyze the stacked bio-signal from a user's daily life and can prescribe for personal living. For the verification of the implemented homecare kit, a sleep apnea patient actually wore our homecare kit and polysomnography equipment simultaneously in the hospital. We evaluated the equipment equivalence based on the analysis result and acquisition bio-signal.