Multimodal Wearable Sensors for Human-Machine Interfaces

Certain areas of the body, such as the hands, eyes and organs of speech production, provide high-bandwidth information channels from the conscious mind to the outside world. The objective of this research was to develop an innovative wearable sensor device that records signals from these areas more conveniently than has previously been possible, so that they can be harnessed for communication. A novel bioelectrical and biomechanical sensing device, the wearable endogenous biosignal sensor (WEBS), was developed and tested in various communication and clinical measurement applications. One ground-breaking feature of the WEBS system is that it digitises biopotentials almost at the point of measurement. Its electrode connects directly to a high-resolution analog-to-digital converter. A second major advance is that, unlike previous active biopotential electrodes, the WEBS electrode connects to a shared data bus, allowing a large or small number of them to work together with relatively few physical interconnections. Another unique feature is its ability to switch dynamically between recording and signal source modes. An accelerometer within the device captures real-time information about its physical movement, not only facilitating the measurement of biomechanical signals of interest, but also allowing motion artefacts in the bioelectrical signal to be detected. Each of these innovative features has potentially far-reaching implications in biopotential measurement, both in clinical recording and in other applications. Weighing under 0.45 g and being remarkably low-cost, the WEBS is ideally suited for integration into disposable electrodes. Several such devices can be combined to form an inexpensive digital body sensor network, with shorter set-up time than conventional equipment, more flexible topology, and fewer physical interconnections. One phase of this study evaluated areas of the body as communication channels. The throat was selected for detailed study since it yields a range of voluntarily controllable signals, including laryngeal vibrations and gross movements associated with vocal tract articulation. A WEBS device recorded these signals and several novel methods of human-to-machine communication were demonstrated. To evaluate the performance of the WEBS system, recordings were validated against a high-end biopotential recording system for a number of biopotential signal types. To demonstrate an application for use by a clinician, the WEBS system was used to record 12‑lead electrocardiogram with augmented mechanical movement information

WEARABLE MULTI-SENSOR SYSTEM FOR TELEMEDICINE APPLICATIONS

In this paper, we describe a technical design of wearable multi-sensor systems for physiological data measurement and wide medical applications, significantly impacted in telehealth. The monitors are composed of three analog front-end (AFE) devices, which assist with interfacing digital electronics to the noise-, time-sensitive physiological sensors for measuring ECG (heart-rate monitor), RR (respiration-rate monitor), SRL (skin resistivity monitor). These three types of sensors can be used separately or together and allow to determine a number of parameters for the assessment of mental and physical condition. The system is designed based on requirements for demanding environments even outside the realm of medical applications, and in accordance with Health and Safety at Work directives (89/391/CE and Seveso-II 96/82/EC) for occupational hygiene, medical, rehabilitation, sports and fitness applications

Conditioning electrical impedance mammography system

A multi-frequency Electrical Impedance Mammography (EIM) system has been developed to evaluate the conductivity and permittivity spectrums of breast tissues, which aims to improve early detection of breast cancer as a non-invasive, relatively low cost and label-free screening (or pre-screening) method. Multi-frequency EIM systems typically employ current excitations and measure differential potentials from the subject under test. Both the output impedance and system performance (SNR and accuracy) depend on the total output resistance, stray and output capacitances, capacitance at the electrode level, crosstalk at the chip and PCB levels. This makes the system design highly complex due to the impact of the unwanted capacitive effects, which substantially reduce the output impedance of stable current sources and bandwidth of the data that can be acquired. To overcome these difficulties, we present new methods to design a high performance, wide bandwidth EIM system using novel second generation current conveyor operational amplifiers based on a gyrator (OCCII-GIC) combination with different current excitation systems to cancel unwanted capacitive effects from the whole system. We reconstructed tomography images using a planar E-phantom consisting of an RSC circuit model, which represents the resistance of extra-cellular (R), intra-cellular (S) and membrane capacitance (C) of the breast tissues to validate the performance of the system. The experimental results demonstrated that an EIM system with the new design achieved a high output impedance of 10MΩ at 1MHz to at least 3MΩ at 3MHz frequency, with an average SNR and modelling accuracy of over 80dB and 99%, respectively

Low Power Circuits for Smart Flexible ECG Sensors

Cardiovascular diseases (CVDs) are the world leading cause of death. In-home heart condition monitoring effectively reduced the CVD patient hospitalization rate. Flexible electrocardiogram (ECG) sensor provides an affordable, convenient and comfortable in-home monitoring solution. The three critical building blocks of the ECG sensor i.e., analog frontend (AFE), QRS detector, and cardiac arrhythmia classifier (CAC), are studied in this research. A fully differential difference amplifier (FDDA) based AFE that employs DC-coupled input stage increases the input impedance and improves CMRR. A parasitic capacitor reuse technique is proposed to improve the noise/area efficiency and CMRR. An on-body DC bias scheme is introduced to deal with the input DC offset. Implemented in 0.35m CMOS process with an area of 0.405mm2, the proposed AFE consumes 0.9W at 1.8V and shows excellent noise effective factor of 2.55, and CMRR of 76dB. Experiment shows the proposed AFE not only picks up clean ECG signal with electrodes placed as close as 2cm under both resting and walking conditions, but also obtains the distinct -wave after eye blink from EEG recording. A personalized QRS detection algorithm is proposed to achieve an average positive prediction rate of 99.39% and sensitivity rate of 99.21%. The user-specific template avoids the complicate models and parameters used in existing algorithms while covers most situations for practical applications. The detection is based on the comparison of the correlation coefficient of the user-specific template with the ECG segment under detection. The proposed one-target clustering reduced the required loops. A continuous-in-time discrete-in-amplitude (CTDA) artificial neural network (ANN) based CAC is proposed for the smart ECG sensor. The proposed CAC achieves over 98% classification accuracy for 4 types of beats defined by AAMI (Association for the Advancement of Medical Instrumentation). The CTDA scheme significantly reduces the input sample numbers and simplifies the sample representation to one bit. Thus, the number of arithmetic operations and the ANN structure are greatly simplified. The proposed CAC is verified by FPGA and implemented in 0.18m CMOS process. Simulation results show it can operate at clock frequencies from 10KHz to 50MHz. Average power for the patient with 75bpm heart rate is 13.34W

Development of real-time cellular impedance analysis system

The cell impedance analysis technique is a label-free, non-invasive method, which simplifies sample preparation and allows applications requiring unmodified cell retrieval. However, traditional impedance measurement methods suffer from various problems (speed, bandwidth, accuracy) for extracting the cellular impedance information. This thesis proposes an improved system for extracting precise cellular impedance in real-time, with a wide bandwidth and satisfactory accuracy. The system hardware consists of five main parts: a microelectrode array (MEA), a stimulation circuit, a sensing circuit, a multi-function card and a computer. The development of system hardware is explored. Accordingly, a novel bioimpedance measurement method coined digital auto balancing bridge method, which is improved from the traditional analogue auto balancing bridge circuitry, is realized for real-time cellular impedance measurement. Two different digital bridge balancing algorithms are proposed and realized, which are based on least mean squares (LMS) algorithm and fast block LMS (FBLMS) algorithm for single- and multi-frequency measurements respectively. Details on their implementation in FPGA are discussed. The test results prove that the LMS-based algorithm is suitable for accelerating the measurement speed in single-frequency situation, whilst the FBLMS-based algorithm has advantages in stable convergence in multi-frequency applications. A novel algorithm, called the All Phase Fast Fourier Transform (APFFT), is applied for post-processing of bioimpedance measurement results. Compared with the classical FFT algorithm, the APFFT significantly reduces spectral leakage caused by truncation error. Compared to the traditional FFT and Digital Quadrature Demodulation (DQD) methods, the APFFT shows excellent performance for extracting accurate phase and amplitude in the frequency spectrum. Additionally, testing and evaluation of the realized system has been performed. The results show that our system achieved a satisfactory accuracy within a wide bandwidth, a fast measurement speed and a good repeatability. Furthermore, our system is compared with a commercial impedance analyzer (Agilent 4294A) in biological experiments. The results reveal that our system achieved a comparable accuracy to the commercial instrument in the biological experiments. Finally, conclusions are given and the future work is proposed

Towards wearable spectroscopy bioimpedance applications: power management for a battery driven impedance meter

Projecte realitat en col.laboració amb el centre Hogskolan i Boras (Suècia)In recent years, due to the combination of technological advances in the fields of measurement instrumentation, communications, home-health care and textile-technology the development of medical devices has shifted towards applications of personal healthcare. There are well known the available solutions for heart rate monitoring successfully provided by Polar and Numetrex. Furthermore new monitoring applications are also investigated. Among these non-invasive monitoring applications, it is possible to find several ones enable by measurements of Electrical Bioimpedance. Analog Devices has developed the AD5933 Impedance Network Analyzer which facilitates to a large extent the design and implementation of Electrical Bioimpedance Spectrometers in a much reduced space. Such small size allows the development of a fully wearable bioimpedance measurement. With the development of a Electrical Bioimpedance-enable wearable medical device in focus for personal healthcare monitoring, in this project, the issue of power management has been targeted and a battery-driven Electrical Bioimpedance Spectrometer based in the AD5933 has been implemented. The resulting system has the possibility to operate with a Li-Po battery with a power autonomy over 17 hours

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

A novel approach to bioelectrical impedance plethysmography for the assessment of arterial and venous circulatory problems in the forearm

Peripheral vascular disease (PVD) and/or peripheral arterial disease (PAD) are sicknesses known to inadequate delivery of either arterial or venous blood towards the extremities. Such sickness may trigger complications owing to the lack of transport of oxygen and nutrients, thus causing hypoxic events that may eventually prompt to ischaemic tissue or even the loss of the compromised limb. One of the most prominent indicators of prosperous health is blood volume and flow. The basic information within these health parameters may show cardiovascular problems or the advance of further complications related to other diseases like diabetes. In clinical setting, there effective methods to measure these parameters like Doppler ultrasound, photoplethysmography or venous occlusion plethysmography. These methods take measurements from either single vessels and/or small volume of tissue. However, it is difficult to establish a relation between the obstruction of arterial and/or venous circulation and the amount of blood received by the tissue. Bioelectrical impedance plethysmography (iPG) measures blood changes by driving a small amount of AC current into the body and after measuring the potential created by fluids flowing through tissue. This technique apart from taking measures within defined volumes of tissue, it is easy to use as only needs four electrodes on the skin. Hence, a bespoken bioelectrical impedance device including hardware and software was built ready to measure changes in blood volume/flow in the upper limbs. The system was assessed in an in-vivo controlled environment with 8 participants. The blood flow towards their left arms was altered by constricting the upper arm with a cuff at three levels: 1) below venous pressure 2) amongst venous and arterial pressure and 3) during total occlusion. Simultaneously, measurements from various instruments like ECG, Doppler ultrasound, laser Doppler flowmetry and PPG were taken and compared to the measurements obtained from the iPG instrument and defining its correlation with the impedimetric signal. The results from the experiments showed that the bioelectrical impedance signal changed in basal and arterial pulses showing specific characteristics for each kind of occlusion. The data indicated that it is possible to differentiate between a venous and arterial occlusion by examining both components of the impedance signal. The impedance during venous occlusion dropped in average 0.658±0.230% from the baseline. On the other hand, during arterial occlusion the base impedance dropped in a higher rate approximately 1.13±04.82%, indicating a differentiator during both type of blood flow disruption. Furthermore, the impedance plethysmography waveform morphology also reshaped during these occlusive periods. The whole waveform during artificial venous obstruction increased in magnitude, the systolic peak rose 31.80%, the dicrotic notch 47.73% and the diastolic point 31.92%, where the value of the latter was higher than the dicrotic notch point. In contrast, in the time of partial arterial occlusion the waveform also increased in size at all these points, but its shape was altered. The impedance magnitude at the diastolic point went below the ones at the dicrotic notch. These fluctuations provided additional further information that it might be possible to differentiate amongst venous and arterial occlusions. By consolidating the data obtained by the iPG device, it is possible to produce an index ratio between the basal impedance and these three reference points which may help to identify early circulatory problems in the arterial and/or venous systems

The Investigation and Implementation of electrical Impedance Tomography Hardware System

Electrical impedance tomography (EIT) is a medical imaging technology that provides a tomographic representation of the distribution of electrical impedance within the body. As the electrical impedance varies for different body tissues, it is possible to characterize tissues from the images and to detect physiological events. EIT systems have been developed from applying a single signal frequency to a range of frequencies. Imaging at multiple frequencies significantly improves the ability to characterize and differentiate heterogeneity within the region of interest. Applications of EIT are limited by its poor resolution as a consequence of limited number of electrodes and lack of independently published measurements. In a practical EIT system design the parallel structure is normally adopted as it provides a real time monitoring structure. However, there is a difficulty in expanding to a 2-dimensitional or 3-dimensitional high resolution imaging system, as the number of electrodes increase. In this thesis, a serial structure spectrum EIT system has been investigated and developed. Modelling of the electrical circuit has shown that the system bandwidth is degraded primarily by the signal transmission in the coaxial cable and multiplexer. To remove the capacitive effect of these components, a distribute system concept has been developed. The concept uses active electrodes in which a current source and a front end amplifier are embedded in the electrode which makes direct contact with the tissue being measured. The active electrode is based on the Howland current source. The required high output impedance of Howland current source can be realised by matching the two resistor arms. However, from the electrical equivalent circuit analysis the actual output impedance of this circuit was found to be degraded by the op-amp' s limited open loop gain, especially at higher frequencies. To solve the problem, the author describes in detail a novel method of compensating for the above effects. Subsequent circuit tests showed significant improvement after the compensation. Further, to improve the small signal noise ratio a programmable gain amplifier to adapt the frame data measurement was developed. These developments have led to the feasibility of active electrodes. The thesis describes in detail the development, of the MK2 EIT system which is presented as the output of this research

Low Power Skin Impedance Spectrometer

Non-invasive diagnosing is becoming a growing trend in the Medical Field, and as a result devices that do apply these non-invasive diagnoses must be developed. This project developed a medical device that measures the skin’s impedance and Phase accurately via Bluetooth graphs the results on a computer. The designed achieved is capable of measuring impedance from 200 to 3000 Ohms. This allows the project to be used for the following applications: BIA, pain sensing and diabetes diagnosis