A Hybrid-Powered Wireless System for Multiple Biopotential Monitoring

Chronic diseases are the top cause of human death in the United States and worldwide. A huge amount of healthcare costs is spent on chronic diseases every year. The high medical cost on these chronic diseases facilitates the transformation from in-hospital to out-of-hospital healthcare. The out-of-hospital scenarios require comfortability and mobility along with quality healthcare. Wearable electronics for well-being management provide good solutions for out-of-hospital healthcare. Long-term health monitoring is a practical and effective way in healthcare to prevent and diagnose chronic diseases. Wearable devices for long-term biopotential monitoring are impressive trends for out-of-hospital health monitoring. The biopotential signals in long-term monitoring provide essential information for various human physiological conditions and are usually used for chronic diseases diagnosis. This study aims to develop a hybrid-powered wireless wearable system for long-term monitoring of multiple biopotentials. For the biopotential monitoring, the non-contact electrodes are deployed in the wireless wearable system to provide high-level comfortability and flexibility for daily use. For providing the hybrid power, an alternative mechanism to harvest human motion energy, triboelectric energy harvesting, has been applied along with the battery to supply energy for long-term monitoring. For power management, an SSHI rectifying strategy associated with triboelectric energy harvester design has been proposed to provide a new perspective on designing TEHs by considering their capacitance concurrently. Multiple biopotentials, including ECG, EMG, and EEG, have been monitored to validate the performance of the wireless wearable system. With the investigations and studies in this project, the wearable system for biopotential monitoring will be more practical and can be applied in the real-life scenarios to increase the economic benefits for the health-related wearable devices

Perustason vaellush äiri on v ähentäminen elektrokardiografiassa Kalman-suotimilla

Developments in sensor technology have enabled the continuous electrocardiography monitoring during daily activities. These recordings can be valuable in the detection of arrhythmias and abnormal cardiac cycles that occur only under certain circumstances or infrequently. Unfortunately, the activities of the patient cause severe motion artifacts to the ECG signal that affect the signal quality and complicate the signal interpretation. The motion based baseline wander artifact can be reduced to a certain point by improving the stability of the electrode-skin interface. However, also computational signal processing methods, like adaptive filtering, are needed. The signal processing methods can be improved by utilizing additional variables that correlate with the artifact sources. For example, acceleration and impedance signals have been studied as possible references of motion. However, being able to do the measurements without additional sensors would enable the measurement device to be simpler, lighter, and lower in cost. This thesis presents an accelerometer-free ECG signal baseline wander reduction algorithm that uses electromyography signal as a Kalman filter reference signal. The EMG signal is extracted from the ECG signal itself and used as an estimate of local electrode motion. The motion estimate is then used as a reference signal for an adaptive Kalman filter baseline wander compensation algorithm. The algorithm is evaluated on data collected in clinical trials. In addition, the feasibility of removing the baseline wander using a reduced number of accelerometers as a motion reference for Kalman filter is studied. The results showed that the proposed method removed baseline wander successfully and without significant alterations in the signal morphology. The method proved to be at least equally proficient with the methods it was compared to. The results suggested that the baseline wander reduction from ambulatory ECG measurements could be achieved without additional sensors using EMG signal as a motion reference for the Kalman filter. In addition, also the reduced number of accelerometers proved to be a feasible source of the motion reference signal.Sensoriteknologian kehitys on mahdollistanut sydänsähkökäyrän jatkuvan mittaamisen päivittäisten aktiviteettien aikana. Jatkuvat mittaukset voivat auttaa havaitsemaan sellaisia rytmihäiriöitä ja epänormaaleja sydämen toimintakiertoja, jotka esiintyvät vain tietyissä olosuhteissa tai epäsäännöllisesti. Potilaan liikkeet kuitenkin aiheuttavat sydänsähkökäyrään voimakkaita liikeartefakteja, jotka heikentävät signaalin laatua ja vaikeuttavat signaalin tulkintaa. Liikkeestä aiheutuvaa perustason vaellushäiriötä voidaan hieman vähentää parantamalla ihon ja elektrodin välisen rajapinnan vakautta. Kuitenkin myös laskennallisia signaalinkäsittelymenetelmiä kuten adaptiivisia suotimia tarvitaan. Signaalinkäsittelymenetelmiä voidaan tehostaa hyödyntämällä lisämittaussuureita, jotka korreloivat artefaktien lähteen kanssa. Esimerkiksi kiihtyvyys- ja impedanssisignaaleja on tutkittu mahdollisina liikereferensseinä. Tässä diplomityössä ehdotetaan perustason vaellushäiriön vähentämiseen sydänsähkökäyrästä menetelmää, joka ei hyödynnä lisäsensoreita, vaan käyttää lihassähkökäyrää Kalman-suotimen liike-estimaattina. Lihassähkökäyrä erotetaan sydänsähkökäyrästä ja sitä käytetään estimaattina elektrodien paikallisesta liikkeestä. Liike-estimaattia puolestaan hyödynnetään adaptiiviseen Kalman-suotimeen perustuvan perustason vaellushäiriön kompensaatioalgoritmin referenssisignaalina. Algoritmi arvioidaan kliinisissä kokeissa kerätyllä datalla. Lisäksi tutkitaan Kalman-suotimen toimivuutta käytettäessä pienempää määrää kiihtyvyysantureita liike-estimaatin lähteenä. Tulokset osoittivat, että ehdotettu menetelmä poisti onnistuneesti perustason vaellushäiriön muuttamatta signaalin muotoa merkittävästi. Ehdotettu menetelmä osoittautui toimivan vähintään yhtä hyvin kuin menetelmät, joihin sitä verrattiin. Tulosten mukaan perustason vaellushäiriön vähentäminen liikkeen aikaisista sydänsähkökäyrämittauksista olisi mahdollista ilman lisäsensoreita käyttämällä lihassähkökäyrää Kalman-suotimen liikereferenssinä. Lisäksi, vähennetty määrä kiihtyvyysantureita osoittautui myös toimivaksi liike-estimaatin lähteeksi

Development of a hybrid assist-as-need hand exoskeleton for stroke rehabilitation.

Stroke is one of the leading causes of disability globally and can significantly impair a patient’s ability to function on a daily basis. Through physical rehabilitative measures a patient may regain a level of functional independence. However, required therapy dosages are often not met. Rehabilitation is typically implemented through manual one-to-one assistance with a physiotherapist, which quickly becomes labour intensive and costly. Hybrid application of functional electrical stimulation (FES) and robotic support can access the physiological benefits of direct muscle activation while providing controlled and repeatable motion assistance. Furthermore, patient engagement can be heightened through the integration of a volitional intent measure, such as electromyography (EMG). Current hybrid hand-exoskeletons have demonstrated that a balanced hybrid support profile can alleviate FES intensity and motor torque requirements, whilst improving reference tracking errors. However, these support profiles remain fixed and patient fatigue is not addressed. The aim of this thesis was to develop a proof-of-concept assist-as-need hybrid exoskeleton for post-stroke hand rehabilitation, with fatigue monitoring to guide the balance of support modalities. The device required the development and integration of a constant current (CC) stimulator, stimulus-resistant EMG device, and hand-exoskeleton. The hand exoskeleton in this work was formed from a parametric Watt I linkage model that adapts to different finger sizes. Each linkage was optimised with respect to angular precision and compactness using Differential Evolution (DE). The exoskeleton’s output trajectory was shown to be sensitive to parameter variation, potentially caused by finger measurement error and shifts in coupler placement. However, in a set of cylindrical grasping trials it was observed that a range of movement strategies could be employed towards a successful grasp. As there are many possible trajectories that result in a successful grasp, it was deduced that the exoskeleton can still provide functional assistance despite its sensitivity to parameter variation. The CC stimulator developed in this work has a part cost of USD $145 and allows flexible adjustment of waveform parameters through an on-board micro-controller. The device is designed to output current up to ±30mA given a voltage compliance of ±50V. When applied across a 2kΩ load, the device exhibited a linear output transfer function, with a maximum ramp tracking error of 5 The stimulus-resistant EMG device builds on current designs by using a novel Schmitt trigger based artefact detection channel to adaptively blank stimulation artefacts without stimulator synchronisation. The design has a part cost of USD$150 and has been made open-source. The device demonstrated its ability to record EMG over its predominant energy spectrum during stimulation, through the stimulation electrodes or through separate electrodes. Pearson’s correlation coefficients greater than 0.84 were identified be- tween the normalised spectra of volitional EMG (vEMG) estimates during stimulation and of stimulation-free EMG recordings. This spectral similarity permits future research into applications such as spectral-based monitoring of fatigue and muscle coherence, posing an advantage over current same-electrode stimulation and recording systems, which can- not sample the lower end of the EMG spectrum due to elevated high-pass filter cut-off frequencies. The stimulus-resistant EMG device was used to investigate elicited EMG (eEMG)-based fatigue metrics during vEMG-controlled stimulation and hybrid support profiles. During intermittent vEMG-controlled stimulation, the eEMG peak-to-peak amplitude (PTP) index was the median frequency (MDF) had a negative correlation for all subjects with R > 0:62 during stimulation-induced wrist flexion and R > 0:55 during stimulation-induced finger flexion. During hybrid FES-robotic support trials, a 40% reduction in stimulus intensity resulted in an average 21% reduction in MDF gradient magnitudes. This reflects lower levels of fatigue during the hybrid support profile and indicates that the MDF gradient can provide useful information on the progression of muscle fatigue. A hybrid exoskeleton system was formed through the integration of the CC stimulator, stimulus-resistant EMG device, and the hand exoskeleton developed in this work. The system provided assist-as-need functional grasp assistance through stimulation and robotic components, governed by the user’s vEMG. The hybrid support profile demonstrated consistent motion assistance with lowered stimulation intensities, which in-turn lowered the subjects’ perceived levels of fatigue

Characterisation and biomedical application of fabric sensors

The sensors commonly used today to measure human physiological parameters are hard and discrete and not suitable for long term monitoring. A wearable garment with integrated fabric sensors incorporated in an unobtrusive way is highly desirable for long term physiological monitoring, particularly in a non-clinical environment. The aim of this work is to investigate fabric sensors which can be integrated into a garment to allow the unobtrusive monitoring of physiological parameters, primarily for measuring the electrocardiograph (ECG) and respiration. The work focuses on using only dry fabric electrodes where skin preparation and the use of chemical gels or adhesives are not employed. The textile structure used in this study was designed to provide controlled contact pressure, enable construction using common textile processing methods, allow accurate placement of electrodes on the body, allow comfortable fit and be unobtrusive to wear. It was decided to use the knitting method to make bands which incorporated conductive electrodes in order to evaluate different fabric electrodes materials. The detection of respiration using fabric strain sensors did not require electrical contact with the skin. Preliminary experiments were conducted on a single subject to develop a device and methodology. Galvanic skin response and ECG was initially investigated to determine the effectiveness of electrode materials. ECG was established as a more reliable measure and was subsequently used to evaluate the initial performance of the fabric electrodes, and further refine the test methodology on a single subject. Experiments were then conducted on 10 male volunteer participants of reasonable general health having no known heart conditions, with ages 30-55 and BMI 20-30. It was found that fabric sensors which were soft, pliable and flexible have advantages in terms of ability to provide better quality ECG signals and a comfortable bio-interface. Variation in the pressure applied to the electrode directly affects the acquired signal level and a pressure of 2.5KPa is preferred. Multifilament conductive yarns are more easily processed into fabric than monofilament yarns and are generally preferred. Electrodes comprising a conductive polymer treated fabric gave better performance than metal or metal coated yarns. Fabric strain sensors were tested and used to detect respiration on a single subject. It was found that human respiration can be measured using strain sensors such as those comprised of a conductive polymer treated fabric or a fabric incorporating a rigid conductive monofilament fibre

Robust Algorithms for Unattended Monitoring of Cardiovascular Health

Cardiovascular disease is the leading cause of death in the United States. Tracking daily changes in one’s cardiovascular health can be critical in diagnosing and managing cardiovascular disease, such as heart failure and hypertension. A toilet seat is the ideal device for monitoring parameters relating to a subject’s cardiac health in his or her home, because it is used consistently and requires no change in daily habit. The present work demonstrates the ability to accurately capture clinically relevant ECG metrics, pulse transit time based blood pressures, and other parameters across subjects and physiological states using a toilet seat-based cardiovascular monitoring system, enabled through advanced signal processing algorithms and techniques. The algorithms described herein have been designed for use with noisy physiologic signals measured at non-standard locations. A key component of these algorithms is the classification of signal quality, which allows automatic rejection of noisy segments before feature delineation and interval extractions. The present delineation algorithms have been designed to work on poor quality signals while maintaining the highest possible temporal resolution. When validated on standard databases, the custom QRS delineation algorithm has best-in-class sensitivity and precision, while the photoplethysmogram delineation algorithm has best-in-class temporal resolution. Human subject testing on normative and heart failure subjects is used to evaluate the efficacy of the proposed monitoring system and algorithms. Results show that the accuracy of the measured heart rate and blood pressure are well within the limits of AAMI standards. For the first time, a single device is capable of monitoring long-term trends in these parameters while facilitating daily measurements that are taken at rest, prior to the consumption of food and stimulants, and at consistent times each day. This system has the potential to revolutionize in-home cardiovascular monitoring

DICOM for EIT

With EIT starting to be used in routine clinical practice [1], it important that the clinically relevant information is portable between hospital data management systems. DICOM formats are widely used clinically and cover many imaging modalities, though not specifically EIT. We describe how existing DICOM specifications, can be repurposed as an interim solution, and basis from which a consensus EIT DICOM ‘Supplement’ (an extension to the standard) can be writte

INTEGRATED MICROSYSTEM-BASED APPROACH FOR DETECTION AND TREATMENT OF BACTERIAL BIOFILMS ON URINARY CATHETERS

Biofilms are a ubiquitous mode of growth for bacteria and present a significant challenge in healthcare due to their resistant nature towards traditional antibiotic therapy. Particularly, biofilms can form on indwelling urinary catheters, leading to catheter-associated urinary tract infections, which are one of the most prevalent healthcare-acquired infections. In recent years, microsystems-based approaches have been developed to measure and study bacterial biofilms. In this dissertation, microsystems are adapted for the catheterized urinary tract environment to address biofilm infections in situ. Specifically, a proof-of-concept device comprised of gold interdigitated electrodes on a flexible polyimide substrate is fabricated and characterized in vitro. This substrate allows the device to conform seamlessly with the cylindrical surface of a catheter. Real-time impedance sensing is demonstrated, showing an average decrease in impedance of 30.3% following 24 hours of biofilm growth. The device also applies the bioelectric effect, which yields an increase in impedance of 12% and the lowest biomass relative to control treatments. Furthermore, 3D-printed molds and commercial modeling software show that the cylindrical conformation does not have an appreciable impact on performance. This device is integrated with a commercially available Foley catheter using two disparate approaches: (1) integration of the flexible proof-of-concept device using a 3D-printed catheter insert and (2) electroless plating directly onto the catheter lumen. In addition to electrode integration, miniaturized electronic systems are developed to control sensing and treatment wirelessly with a minimal form factor. A smartphone mobile application is developed in conjunction with this effort, to provide a user-friendly interface for the system. Several functions are verified with the integrated system, including biofilm sensing, wireless signal transmission, bladder drainage, and balloon inflation. To decrease the risk associated with this system for future research in vivo and in a clinical setting, sensing and treatment are evaluated under realistic conditions. The biochemical aspect of the catheterized environment is recreated using artificial urine, and the physical aspect is recreated using a silicone model of a human bladder and a programmable pump. A 13.0% decrease in impedance is associated with bacterial growth; this decreased magnitude relative to the proof-of-concept device is due to the reduced degree of growth in artificial urine. The bioelectric effect is demonstrated as well, showing a reduction in planktonic bacteria of 1.50×107 CFU/ml and adhered biomass equivalent to OD590nm = 0.072 relative to untreated samples. This work provides a framework for developing microsystem-based tools for biofilm infection management and research from proof-of-concept to integrated system, particularly for CAUTI. The results demonstrate that the cylindrical conformation does not interfere with device sensing or treatment performance and that the system maintains functionality under realistic conditions, laying the groundwork for future in vivo and clinical testing. The system will provide in situ and real-time data regarding catheter biofilm colonization in a way that is not possible with existing techniques. Finally, the system can serve to reduce reliance on antibiotics and reduce the spread of antibiotic resistance in CAUTI and other vulnerable areas