Design and Implementation of a Wireless Charging-Based Cardiac Monitoring System Focused on Temperature Reduction and Robust Power Transfer Efficiency

Wireless power transfer systems are increasingly used as a means of charging implantable medical devices. However, the heat or thermal radiation from the wireless power transfer system can be harmful to biological tissue. In this research, we designed and implemented a wireless power transfer system-based implantable medical device with low thermal radiation, achieving 44.5% coil-to-coil efficiency. To suppress thermal radiation from the transmitting coil during charging, we minimized the ESR value of the transmitting coil. To increase power transfer efficiency, a ferrite film was applied on the receiving part. Based on analyses, we fabricated a cardiac monitoring system with dimensions of 17 x 24 x 8 mm(3) and implanted it in a rat. We confirmed that the temperature of the wireless charging device increased by only 2 degrees C during the 70 min charging, which makes it safe enough to use as an implantable medical device charging system.11Ysciescopu

Use of location data for the surveillance, analysis, and optimization of clinical processes

Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology, 2006.Includes bibliographical references (leaves 33-35).Location tracking systems in healthcare produce a wealth of data applicable across many aspects of care and management. However, since dedicated location tracking systems, such as the oft mentioned RFID tracking system, are still sparsely deployed, a number of other data sources may be utilized to serve as a proxy for physical location, such as barcodes and manual timestamp entry, and may be better suited to indicate progress through clinical workflows. INCOMING!, a web-based platform that monitors and tracks patient progress from the operating room to the post-anesthesia care unit (PACU), is one such system that utilizes manual timestamps routinely entered as standard process of care in the operating room in order to track a patient's progress through the post-operative period. This integrated real time system facilitates patient flow between the PACU and the surgical ward and eases PACU workload by reducing the effort of discharging patients.(cont.) We have also developed a larger-scale integrated system for perioperative processes that integrates perioperative data from anesthesia and surgical devices and operating room (OR) / hospital information systems, and projects the real-time integrated data as a single, unified, easy to visualize display. The need to optimize perioperative throughput creates a demand for integration of the datastreams and for timely data presentation. The system provides improved context-sensitive information display, improved real-time monitoring of physiological data, real-time access to readiness information, and improved workflow management. These systems provide improved data access and utilization, providing context-aware applications in healthcare that are aware of a user's location, environment, needs, and goals.by Mark A. Meyer.S.M

Improving the mechanistic study of neuromuscular diseases through the development of a fully wireless and implantable recording device

Neuromuscular diseases manifest by a handful of known phenotypes affecting the peripheral nerves, skeletal muscle fibers, and neuromuscular junction. Common signs of these diseases include demyelination, myasthenia, atrophy, and aberrant muscle activity—all of which may be tracked over time using one or more electrophysiological markers. Mice, which are the predominant mammalian model for most human diseases, have been used to study congenital neuromuscular diseases for decades. However, our understanding of the mechanisms underlying these pathologies is still incomplete. This is in part due to the lack of instrumentation available to easily collect longitudinal, in vivo electrophysiological activity from mice. There remains a need for a fully wireless, batteryless, and implantable recording system that can be adapted for a variety of electrophysiological measurements and also enable long-term, continuous data collection in very small animals. To meet this need a miniature, chronically implantable device has been developed that is capable of wirelessly coupling energy from electromagnetic fields while implanted within a body. This device can both record and trigger bioelectric events and may be chronically implanted in rodents as small as mice. This grants investigators the ability to continuously observe electrophysiological changes corresponding to disease progression in a single, freely behaving, untethered animal. The fully wireless closed-loop system is an adaptable solution for a range of long-term mechanistic and diagnostic studies in rodent disease models. Its high level of functionality, adjustable parameters, accessible building blocks, reprogrammable firmware, and modular electrode interface offer flexibility that is distinctive among fully implantable recording or stimulating devices. The key significance of this work is that it has generated novel instrumentation in the form of a fully implantable bioelectric recording device having a much higher level of functionality than any other fully wireless system available for mouse work. This has incidentally led to contributions in the areas of wireless power transfer and neural interfaces for upper-limb prosthesis control. Herein the solution space for wireless power transfer is examined including a close inspection of far-field power transfer to implanted bioelectric sensors. Methods of design and characterization for the iterative development of the device are detailed. Furthermore, its performance and utility in remote bioelectric sensing applications is demonstrated with humans, rats, healthy mice, and mouse models for degenerative neuromuscular and motoneuron diseases

Open Source EEG Platform with Reconfigurable Features for Multiple-Scenarios

Electroencephalogram (EEG) acquisition systems are widely used as diagnostic and research tools. This document shows the implementation of a reconfigurable family of three affordable 8-channels, 24 bits of resolution, EEG acquisition systems intended for a wide variety of research purposes. The three devices offer a modular design and upgradability, permitting changes in the firmware and software. Due to the nature of the Analog Front-End (AFE) used, no high-pass analog filters were implemented, allowing the capture of very low frequency components. Two systems of the family, called “RF-Brain” and “Bluetooth-Brain”, were designed to be light and wireless, planned for experimentation where movement of the subject cannot be restricted. The sample rate in these systems can be configured up to 2000 samples per second (SPS) for the RF-Brain and 250 SPS for the Bluetooth-Brain when the 8 channels are used. If fewer channels are required, the sampling frequency can be higher (up to 4 kSPS or 2 kSPS for 1 channel for RF-Brain and Bluetooth-Brain respectively). The third system, named “USB-Brain”, is a wired device designed for purposes requiring high sampling frequency acquisition and general purpose ports, with sampling rates up to 4 kSPS

Monitoring, diagnosis, and control for advanced anesthesia management

Modern anesthesia management is a comprehensive and the most critical issue in medical care. During the past dacades, a large amount of research works have been focused on the problems of monitoring anesthesia depth, modeling the dynamics of anesthesia patient for the purpose of control, prediction, and diagnosis. Monitoring the anesthesia depth is not only for keeping the patient in adquate anesthesia level but also for preventing the patient from overdosing. Several EEG based indexes have been developed such as the BIS, and Entropy etc. for measuring depth. However, reports mentioned that those indexes in some cases fail in detecting the awareness of the the patient. In this research work, a new EEG based parameter, beta_2/theta-ratio, was introduced as a potential enhancement in measuring anesthesia depth. It was compared to the relative beta-ratio which had been commercially used in the BIS monitor and proved that the beta_2/theta-ratio has improved reliability and sensitivity in detecting the awareness than the beta-ratio does. Traditional modeling, diagnosis and control in anesthesia focus on a one-drug one-outcome scenario. In fact, Anesthesia drugs have impact on multiple outcomes of an anesthesia patient. Due to limited real-time data, real-time modeling in multi-outcome modeling requires low complexity model structures. A method of decision-oriented modeling which employs simplified and combined model functions in a Wiener structure to reduce model complexity was introduced. This model structure was implemented in device level and tested in operation room for real-time anesthesia monitoring, diagnosis, and prediction. Furthermore, the impact of wireless channels on patient control in anesthesia applications was also investigated. Such a system involves communication channels which introduce noises due to quantization, channel noises, and have limited communication bandwidth resources. Usually signal averaging can be used effectively in reducing the noise effects. However, when feedback was intended, we showed that signal averaging will lose its utility substantially. To explain this phenomenon, we analyzed stability margins under signal averaging and derived some optimal strategies for selecting window sizes. Finally, a mathematical model for the auditory system was introduced to characterize the impact of anesthesia on auditory systems, and analyze and diagnose hearing damage. The auditory system was represented by a black-box input-output system with external sound stimuli as the input and the neuron firing rates as the output. Two parallel subsystem models were developed for modeling the auditory system dynamics: an ARX (Auto-Regression with External Input) model for the auditory system under external stimuli and an ARMA (Auto-Regression and Moving Average) model for the spontaneous activities of the neurons on primary auditory cortex. These models provide a quantitative characterization of anesthesia\u27s impacts and diagnosis of hearing loss on auditory transmission channels

Smart vest for respiratory rate monitoring of COPD patients based on non-contact capacitive sensing

In this paper, a first approach to the design of a portable device for non-contact monitoring of respiratory rate by capacitive sensing is presented. The sensing system is integrated into a smart vest for an untethered, low-cost and comfortable breathing monitoring of Chronic Obstructive Pulmonary Disease (COPD) patients during the rest period between respiratory rehabilitation exercises at home. To provide an extensible solution to the remote monitoring using this sensor and other devices, the design and preliminary development of an e-Health platform based on the Internet of Medical Things (IoMT) paradigm is also presented. In order to validate the proposed solution, two quasi-experimental studies have been developed, comparing the estimations with respect to the golden standard. In a first study with healthy subjects, the mean value of the respiratory rate error, the standard deviation of the error and the correlation coefficient were 0.01 breaths per minute (bpm), 0.97 bpm and 0.995 (p < 0.00001), respectively. In a second study with COPD patients, the values were -0.14 bpm, 0.28 bpm and 0.9988 (p < 0.0000001), respectively. The results for the rest period show the technical and functional feasibility of the prototype and serve as a preliminary validation of the device for respiratory rate monitoring of patients with COPD.Ministerio de Ciencia e Innovación PI15/00306Ministerio de Ciencia e Innovación DTS15/00195Junta de Andalucía PI-0010-2013Junta de Andalucía PI-0041-2014Junta de Andalucía PIN-0394-201

Systemwide Clinical Ultrasound Program Development: An Expert Consensus Model.

Clinical ultrasound (CUS) is integral to the practice of an increasing number of medical specialties. Guidelines are needed to ensure effective CUS utilization across health systems. Such guidelines should address all aspects of CUS within a hospital or health system. These include leadership, training, competency, credentialing, quality assurance and improvement, documentation, archiving, workflow, equipment, and infrastructure issues relating to communication and information technology. To meet this need, a group of CUS subject matter experts, who have been involved in institution- and/or systemwide clinical ultrasound (SWCUS) program development convened. The purpose of this paper was to create a model for SWCUS development and implementation

C-Trend parameters and possibilities of federated learning

Abstract. In this observational study, federated learning, a cutting-edge approach to machine learning, was applied to one of the parameters provided by C-Trend Technology developed by Cerenion Oy. The aim was to compare the performance of federated learning to that of conventional machine learning. Additionally, the potential of federated learning for resolving the privacy concerns that prevent machine learning from realizing its full potential in the medical field was explored. Federated learning was applied to burst-suppression ratio’s machine learning and it was compared to the conventional machine learning of burst-suppression ratio calculated on the same dataset. A suitable aggregation method was developed and used in the updating of the global model. The performance metrics were compared and a descriptive analysis including box plots and histograms was conducted. As anticipated, towards the end of the training, federated learning’s performance was able to approach that of conventional machine learning. The strategy can be regarded to be valid because the performance metric values remained below the set test criterion levels. With this strategy, we will potentially be able to make use of data that would normally be kept confidential and, as we gain access to more data, eventually develop machine learning models that perform better. Federated learning has some great advantages and utilizing it in the context of qEEGs’ machine learning could potentially lead to models, which reach better performance by receiving data from multiple institutions without the difficulties of privacy restrictions. Some possible future directions include an implementation on heterogeneous data and on larger data volume.C-Trend-teknologian parametrit ja federoidun oppimisen mahdollisuudet. Tiivistelmä. Tässä havainnointitutkimuksessa federoitua oppimista, koneoppimisen huippuluokan lähestymistapaa, sovellettiin yhteen Cerenion Oy:n kehittämään C-Trend-teknologian tarjoamaan parametriin. Tavoitteena oli verrata federoidun oppimisen suorituskykyä perinteisen koneoppimisen suorituskykyyn. Lisäksi tutkittiin federoidun oppimisen mahdollisuuksia ratkaista yksityisyyden suojaan liittyviä rajoitteita, jotka estävät koneoppimista hyödyntämästä täyttä potentiaaliaan lääketieteen alalla. Federoitua oppimista sovellettiin purskevaimentumasuhteen koneoppimiseen ja sitä verrattiin purskevaimentumasuhteen laskemiseen, johon käytettiin perinteistä koneoppimista. Kummankin laskentaan käytettiin samaa dataa. Sopiva aggregointimenetelmä kehitettiin, jota käytettiin globaalin mallin päivittämisessä. Suorituskykymittareiden tuloksia verrattiin keskenään ja tehtiin kuvaileva analyysi, johon sisältyi laatikkokuvioita ja histogrammeja. Odotetusti opetuksen loppupuolella federoidun oppimisen suorituskyky pystyi lähestymään perinteisen koneoppimisen suorituskykyä. Menetelmää voidaan pitää pätevänä, koska suorituskykymittarin arvot pysyivät alle asetettujen testikriteerien tasojen. Tämän menetelmän avulla voimme ehkä hyödyntää dataa, joka normaalisti pidettäisiin salassa, ja kun saamme lisää dataa käyttöömme, voimme lopulta kehittää koneoppimismalleja, jotka saavuttavat paremman suorituskyvyn. Federoidulla oppimisella on joitakin suuria etuja, ja sen hyödyntäminen qEEG:n koneoppimisen yhteydessä voisi mahdollisesti johtaa malleihin, jotka saavuttavat paremman suorituskyvyn saamalla tietoja useista eri lähteistä ilman yksityisyyden suojaan liittyviä rajoituksia. Joitakin mahdollisia tulevia suuntauksia ovat muun muassa heterogeenisen datan ja suurempien tietomäärien käyttö

Wireless Simultaneous Stimulation-and-Recording Device (SRD) to Train Cortical Circuits in Rat Somatosensory Cortex

The primary goal of this project is to develop a wireless system for simultaneous recording-and-stimulation (SRD) to deliver low amplitude current pulses to the primary somatosensory cortex (SI) of rats to activate and enhance an interhemispheric cortical pathway. Despite the existence of an interhemispheric connection between similar forelimb representations of SI cortices, forelimb cortical neurons respond only to input from the contralateral (opposite side) forelimb and not to input from the ipsilateral (same side) forelimb. Given the existence of this interhemispheric pathway we have been able to strengthen/enhance the pathway through chronic intracortical microstimulation (ICMS) in previous acute experiments of anesthetized rats. In these acute experiments strengthening the interhemispheric pathway also brings about functional reorganization whereby cortical neurons in forelimb cortex respond to new input from the ipsilateral forelimb. Having the ability to modify cortical circuitry will have important applications in stroke patients and could serve to rescue and/or enhance responsiveness in surviving cells around the stroke region. Also, the ability to induce functional reorganization within the deafferented cortical map, which follows limb amputation, will also provide a vehicle for modulating maladaptive cortical reorganization often associated with phantom limb pain leading to reduced pain. In order to increase our understanding of the observed functional reorganization and enhanced pathway, we need to be able to test these observations in awake and behaving animals and eventually study how these changes persist over a prolonged period of time. To accomplish this a system was needed to allow simultaneous recording and stimulation in awake rats. However, no such commercial or research system exists that meets all requirements for such an experiment. In this project we describe the (1) system design, (2) system testing, (3) system evaluation, and (4) system implementation of a wireless simultaneous stimulation-and-recording device (SRD) to be used to modulate cortical circuits in an awake rodent animal model