Concept and development of an autonomous wearable micro-fluidic platform for real time pH sweat analysis

In this work the development of an autonomous, robust and wearable micro-fluidic platform capable of performing on-line analysis of pH in sweat is discussed. Through the means of an optical detection system based on a surface mount light emitting diode (SMD LED) and a light photo sensor as a detector, a wearable system was achieved in which real-time monitoring of sweat pH was performed during 55 minutes of cycling activity. We have shown how through systems engineering, integrating miniaturised electrical components, and by improving the micro-fluidic chip characteristics, the wearability, reliability and performance of the micro-fluidic platform was significantly improved

Development of a Heart Rate Variability Measurement System using Embedded Electronics

Recent advances in embedded electronics have a remarkable influence on the health care system. One of the most important applications is to monitor the health care of the patients at anytime and anyplace. In the last two decades, many researchers have focused mainly on heart rate variability (HRV) measurements. Patient\u27s heart rate variability should be continuously monitored to help them in case of emergency. Under these circumstances, patients are required to have a HRV measuring kit for a constant observation. The proposed project focuses on the development of a heart rate variability measurement system with the use of embedded electronics. This project consists of two systems: transmitter and a receiver side system. The transmitter section composed of sensor, amplifier, processing unit, and display unit, and transmitter module. The sensors, which are pasted on the body, are used to sense the electrical activity of the heart. These electric signals are given to an amplification unit. This amplification unit is designed with IC ADS1293 to amplify and filter the signals, and also reduce the noise. The output of the amplifier is given to the processing unit. Here, the microcontroller is programmed to process the input signal, and calculate the heart rate. The output of the microcontroller is transmitted to the display unit. The display unit shows the current value of the heart rate. The continuous measurement of heart rate variability is done in the transmitter side system. In case of abnormalities, a GSM module is used to transmit the heart rate alert, which has been processed by the control unit, to the user\u27s mobile phone and GSM receiver modem. In the receiver system, GSM receiver modem receives the data and processed with Visual Basic program to display, and, in the mobile phone, data is received and displayed as a text message. This kind of health monitoring system can offer flexibility and cost saving options to both health care professionals and patients

How a Diverse Research Ecosystem Has Generated New Rehabilitation Technologies: Review of NIDILRR’s Rehabilitation Engineering Research Centers

Over 50 million United States citizens (1 in 6 people in the US) have a developmental, acquired, or degenerative disability. The average US citizen can expect to live 20% of his or her life with a disability. Rehabilitation technologies play a major role in improving the quality of life for people with a disability, yet widespread and highly challenging needs remain. Within the US, a major effort aimed at the creation and evaluation of rehabilitation technology has been the Rehabilitation Engineering Research Centers (RERCs) sponsored by the National Institute on Disability, Independent Living, and Rehabilitation Research. As envisioned at their conception by a panel of the National Academy of Science in 1970, these centers were intended to take a “total approach to rehabilitation”, combining medicine, engineering, and related science, to improve the quality of life of individuals with a disability. Here, we review the scope, achievements, and ongoing projects of an unbiased sample of 19 currently active or recently terminated RERCs. Specifically, for each center, we briefly explain the needs it targets, summarize key historical advances, identify emerging innovations, and consider future directions. Our assessment from this review is that the RERC program indeed involves a multidisciplinary approach, with 36 professional fields involved, although 70% of research and development staff are in engineering fields, 23% in clinical fields, and only 7% in basic science fields; significantly, 11% of the professional staff have a disability related to their research. We observe that the RERC program has substantially diversified the scope of its work since the 1970’s, addressing more types of disabilities using more technologies, and, in particular, often now focusing on information technologies. RERC work also now often views users as integrated into an interdependent society through technologies that both people with and without disabilities co-use (such as the internet, wireless communication, and architecture). In addition, RERC research has evolved to view users as able at improving outcomes through learning, exercise, and plasticity (rather than being static), which can be optimally timed. We provide examples of rehabilitation technology innovation produced by the RERCs that illustrate this increasingly diversifying scope and evolving perspective. We conclude by discussing growth opportunities and possible future directions of the RERC program

A versatile wearable based on reconfigurable hardware for biomedical measurements

In this work a versatile hardware platform based on reconfigurable devices is presented. This platform it intended for the acquisition of multiple biosignals, only requiring a reconfiguration to switch applications. This prototype has been combined with graphene-based, flexible electrodes to cover the application to different biosignals presented in this paper, which are electrocardiogram, electrooculogram and electromyogram. The features of this system provide to the user and to medical personnel a complete set of diagnosis tools, available both at home and hospitals, to be used as a triage tool and for remote patient monitoring. Additionally, an Android application has been developed for signal processing and data presentation to the user. The results obtained demonstrate the wide range of possibilities in portable/wearable applications of the combination of reconfigurable devices and flexible electronics, especially for the remote monitoring of patients using multiple biosignals of interest. The versatility of this device makes it a complete set of monitoring tools integrated in a reduced size device

Low cost EEG signal acquisition for health care and person identification

The task of monitoring human health invasively and maintaining the security of any system is challenging in the current scenario. The proposed system integrates the health monitoring and biometric authentication for a healthy as well as secure world. The initial module comprises of analysing the change in EEG signals when blood pressure increases for the sick and elderly people while the latter module for security purposes. EEG signal is acquired from the subject. The acquiring of the signal undergoes several steps which include the filtering and amplification. The alpha wave which is unique is extracted, that avoids spoofing attacks is considered for biometry while the beta waves which alter the state according to the human mind state is considered for health monitoring. Data reduction along with SVM classifier and Hilbert transform is implemented in the proposed model

A Novel Power-Efficient Wireless Multi-channel Recording System for the Telemonitoring of Electroencephalography (EEG)

This research introduces the development of a novel EEG recording system that is modular, batteryless, and wireless (untethered) with the supporting theoretical foundation in wireless communications and related design elements and circuitry. Its modular construct overcomes the EEG scaling problem and makes it easier for reconfiguring the hardware design in terms of the number and placement of electrodes and type of standard EEG system contemplated for use. In this development, portability, lightweight, and applicability to other clinical applications that rely on EEG data are sought. Due to printer tolerance, the 3D printed cap consists of 61 electrode placements. This recording capacity can however extend from 21 (as in the international 10-20 systems) up to 61 EEG channels at sample rates ranging from 250 to 1000 Hz and the transfer of the raw EEG signal using a standard allocated frequency as a data carrier. The main objectives of this dissertation are to (1) eliminate the need for heavy mounted batteries, (2) overcome the requirement for bulky power systems, and (3) avoid the use of data cables to untether the EEG system from the subject for a more practical and less restrictive setting. Unpredictability and temporal variations of the EEG input make developing a battery-free and cable-free EEG reading device challenging. Professional high-quality and high-resolution analog front ends are required to capture non-stationary EEG signals at microvolt levels. The primary components of the proposed setup are the wireless power transmission unit, which consists of a power amplifier, highly efficient resonant-inductive link, rectification, regulation, and power management units, as well as the analog front end, which consists of an analog to digital converter, pre-amplification unit, filtering unit, host microprocessor, and the wireless communication unit. These must all be compatible with the rest of the system and must use the least amount of power possible while minimizing the presence of noise and the attenuation of the recorded signal A highly efficient resonant-inductive coupling link is developed to decrease power transmission dissipation. Magnetized materials were utilized to steer electromagnetic flux and decrease route and medium loss while transmitting the required energy with low dissipation. Signal pre-amplification is handled by the front-end active electrodes. Standard bio-amplifier design approaches are combined to accomplish this purpose, and a thorough investigation of the optimum ADC, microcontroller, and transceiver units has been carried out. We can minimize overall system weight and power consumption by employing battery-less and cable-free EEG readout system designs, consequently giving patients more comfort and freedom of movement. Similarly, the solutions are designed to match the performance of medical-grade equipment. The captured electrical impulses using the proposed setup can be stored for various uses, including classification, prediction, 3D source localization, and for monitoring and diagnosing different brain disorders. All the proposed designs and supporting mathematical derivations were validated through empirical and software-simulated experiments. Many of the proposed designs, including the 3D head cap, the wireless power transmission unit, and the pre-amplification unit, are already fabricated, and the schematic circuits and simulation results were based on Spice, Altium, and high-frequency structure simulator (HFSS) software. The fully integrated head cap to be fabricated would require embedding the active electrodes into the 3D headset and applying current technological advances to miniaturize some of the design elements developed in this dissertation

Remote Screening And Self-Monitoring For Vision Loss Diseases Based On Smartphone Applications

Remote Healthcare Monitoring System (RHMS) represents remote observing of patient’s well-being and providing therapeutic services. Sensors play an essential part in RHMs. They measure the physical parameters and give continuous information to health organizations, doctors. The presence of Smartphones and other portable devices have allowed us to utilize remote healthcare monitoring system for an assortment of structures. Also, Wireless Sensor Network (WSN) advances considered as one of the critical research factor healthcare application for enhancing the standard of living. In this dissertation, I have presented three tiers operating in the remote healthcare monitoring system; the Body Area Network (BAN), the PAN Coordinator and the Back- Medical End System (BMEsys). The three tiers focused on several patients PAN coordinators include the Wireless Sensor Network. The Wireless Sensor Network can be used at the fixed tale-monitor location and periodic measurements. The Personal Digital Assistant (PDA) can be used in patients own home or community setting with continuous measurements and smartphones can be utilized anywhere with full range parameters, and I have provided a meaningful utilization comparison between Wireless Sensor Network, PDA and smartphone in Remote Healthcare Monitoring System (HRMs) architecture design. Evaluate the approaches of the healthcare monitoring system architecture and investigate the use of advanced technologies enabling the patient vital signs and diagnostic medical team in real-time. This dissertation demonstrates that how a Smartphone can be used for medical treatment in the field of Ophthalmology and discussed how a Smartphone and its technology could be used to diagnose loss of eye vision. Most recent smartphones have been equipped with a featured camera with high megapixels and advanced sensors which can be used to record fundus photographs through a slit lamp or record videos from an operating microscope and display images from optical coherence tomography systems and other high-tech devices. The ophthalmologists can share these images and analyze with their colleagues utilizing media sharing applications and make the optimal diagnostic and therapeutic results to diagnose the low vision of patients. At present, three widely used pocket-sized adapters can improve the magnification and lighting of the camera, which enables the smartphones to capture high-quality images of the eye. These are Portable Eye Examination Kit (PEEK), EyeGo, and D-Eye. Peek Adapter consists of a smartphone application and retina adapter which can be clipped onto the device and synchronized with the peek application for sharing and analyzing the images. This adapter can be used by anyone and anywhere in the world to examine eyes. EyeGo is an adapter intended to allow ophthalmologists and healthcare specialists to capture high-quality images of the eye using an ophthalmic lens. D-Eye Adapter is one of the extensively used adapters which yield excellent results. It consists of a portable eye and retinal system that fits onto a smartphone creating a retinal camera for evaluation and screening of the eye. It uses LED lights as a light source and requires no extra power, making it an ideal solution for portable diagnostics. The medical field has widely accepted these adaptors with the smartphones for diagnosing low vision and eye-related infections. In this dissertation, I also provide a meaningful utilization comparison between the smartphone adapters: D-Eye, EyeGo and Portable Eye Examination Kit (PEEK). In this dissertation, I have developed a new App (Remote Healthcare-Monitoring Mobile App) to help patients who have low vision and who are suffering from the diseases which may cause a vision loss. This app is capable of a process, evaluate, interact and store health data which is continuously measured by (Personal Health Monitors). This App can exchange the information directly to the Smartphone users (patients) and the doctor who allows more security and privacy. The idea of the App consists of the following: A Smartphone Application, a Data Collection Center, and Professionals in Ophthalmology. The patient should be registered in the system, for example, (Retina Michigan Center or Glaucoma Michigan Center). After registration, the patient is instructed on how to take photos of his/her eyes correctly, and then use the Smartphone application. The patient takes photos of his/her eyes and sends them to the data collection center, the specialists get access to these data and help in the treatment according to the analysis. Finally, I completed the development of the Mobile app (including the Skype and Viber links), which can help in exchanging the information between the patient and the doctor

Wired, wireless and wearable bioinstrumentation for high-precision recording of bioelectrical signals in bidirectional neural interfaces

It is widely accepted by the scientific community that bioelectrical signals, which can be used for the identification of neurophysiological biomarkers indicative of a diseased or pathological state, could direct patient treatment towards more effective therapeutic strategies. However, the design and realisation of an instrument that can precisely record weak bioelectrical signals in the presence of strong interference stemming from a noisy clinical environment is one of the most difficult challenges associated with the strategy of monitoring bioelectrical signals for diagnostic purposes. Moreover, since patients often have to cope with the problem of limited mobility being connected to bulky and mains-powered instruments, there is a growing demand for small-sized, high-performance and ambulatory biopotential acquisition systems in the Intensive Care Unit (ICU) and in High-dependency wards. Furthermore, electrical stimulation of specific target brain regions has been shown to alleviate symptoms of neurological disorders, such as Parkinson’s disease, essential tremor, dystonia, epilepsy etc. In recent years, the traditional practice of continuously stimulating the brain using static stimulation parameters has shifted to the use of disease biomarkers to determine the intensity and timing of stimulation. The main motivation behind closed-loop stimulation is minimization of treatment side effects by providing only the necessary stimulation required within a certain period of time, as determined from a guiding biomarker. Hence, it is clear that high-quality recording of local field potentials (LFPs) or electrocorticographic (ECoG) signals during deep brain stimulation (DBS) is necessary to investigate the instantaneous brain response to stimulation, minimize time delays for closed-loop neurostimulation and maximise the available neural data. To our knowledge, there are no commercial, small, battery-powered, wearable and wireless recording-only instruments that claim the capability of recording ECoG signals, which are of particular importance in closed-loop DBS and epilepsy DBS. In addition, existing recording systems lack the ability to provide artefact-free high-frequency (> 100 Hz) LFP recordings during DBS in real time primarily because of the contamination of the neural signals of interest by the stimulation artefacts. To address the problem of limited mobility often encountered by patients in the clinic and to provide a wide variety of high-precision sensor data to a closed-loop neurostimulation platform, a low-noise (8 nV/√Hz), eight-channel, battery-powered, wearable and wireless multi-instrument (55 × 80 mm2) was designed and developed. The performance of the realised instrument was assessed by conducting both ex vivo and in vivo experiments. The combination of desirable features and capabilities of this instrument, namely its small size (~one business card), its enhanced recording capabilities, its increased processing capabilities, its manufacturability (since it was designed using discrete off-the-shelf components), the wide bandwidth it offers (0.5 – 500 Hz) and the plurality of bioelectrical signals it can precisely record, render it a versatile tool to be utilized in a wide range of applications and environments. Moreover, in order to offer the capability of sensing and stimulating via the same electrode, novel real-time artefact suppression methods that could be used in bidirectional (recording and stimulation) system architectures are proposed and validated. More specifically, a novel, low-noise and versatile analog front-end (AFE), which uses a high-order (8th) analog Chebyshev notch filter to suppress the artefacts originating from the stimulation frequency, is presented. After defining the system requirements for concurrent LFP recording and DBS artefact suppression, the performance of the realised AFE is assessed by conducting both in vitro and in vivo experiments using unipolar and bipolar DBS (monophasic pulses, amplitude ranging from 3 to 6 V peak-to-peak, frequency 140 Hz and pulse width 100 µs). Under both in vitro and in vivo experimental conditions, the proposed AFE provided real-time, low-noise and artefact-free LFP recordings (in the frequency range 0.5 – 250 Hz) during stimulation. Finally, a family of tunable hardware filter designs and a novel method for real-time artefact suppression that enables wide-bandwidth biosignal recordings during stimulation are also presented. This work paves the way for the development of miniaturized research tools for closed-loop neuromodulation that use a wide variety of bioelectrical signals as control signals.Open Acces

Real-Time Management of Multimodal Streaming Data for Monitoring of Epileptic Patients

This is the Accepted Manuscript version of the following article: I. Mporas, D. Triantafyllopoulos, V. Megalooikonomou, “Real-Time Management of Multimodal Streaming Data for Monitoring of Epileptic Patients”, Journal of Medical Systems, Vol. 40(45), December 2015. The final published versions is available at: https://link.springer.com/article/10.1007%2Fs10916-015-0403-3 © Springer Science+Business Media New York 2015.New generation of healthcare is represented by wearable health monitoring systems, which provide real-time monitoring of patient’s physiological parameters. It is expected that continuous ambulatory monitoring of vital signals will improve treatment of patients and enable proactive personal health management. In this paper, we present the implementation of a multimodal real-time system for epilepsy management. The proposed methodology is based on a data streaming architecture and efficient management of a big flow of physiological parameters. The performance of this architecture is examined for varying spatial resolution of the recorded data.Peer reviewedFinal Accepted Versio

Beyond solid-state lighting: Miniaturization, hybrid integration, and applications og GaN nano- and micro-LEDs

Gallium Nitride (GaN) light-emitting-diode (LED) technology has been the revolution in modern lighting. In the last decade, a huge global market of efficient, long-lasting and ubiquitous white light sources has developed around the inception of the Nobel-price-winning blue GaN LEDs. Today GaN optoelectronics is developing beyond lighting, leading to new and innovative devices, e.g. for micro-displays, being the core technology for future augmented reality and visualization, as well as point light sources for optical excitation in communications, imaging, and sensing. This explosion of applications is driven by two main directions: the ability to produce very small GaN LEDs (microLEDs and nanoLEDs) with high efficiency and across large areas, in combination with the possibility to merge optoelectronic-grade GaN microLEDs with silicon microelectronics in a fully hybrid approach. GaN LED technology today is even spreading into the realm of display technology, which has been occupied by organic LED (OLED) and liquid crystal display (LCD) for decades. In this review, the technological transition towards GaN micro- and nanodevices beyond lighting is discussed including an up-to-date overview on the state of the art