Brain state monitoring for the future prediction of migraine attacks.

BACKGROUND: Migraine attacks are unpredictable, precluding preemptive interventions and leading to lack of control over individuals' lives. Although there are neurophysiological changes 24-48 hours before migraine attacks, so far, they have not been used in patients' management. This study evaluates the applicability and the ability to identify pre-attack changes of daily "at home" electroencephalography obtained with a portable system for migraine patients. METHODS: Patients with episodic migraine fulfilling ICHD-3 beta criteria used a mobile system composed of a wireless EEG device (BrainStation®, Neuroverse®, Inc., USA) and mobile application (BrainVitalsM®, Neuroverse®, Inc., USA) to self-record their neural activity daily at home while resting and while performing an attention task, over the course of 2 weeks. Standard EEG spectral analysis and event-related brain potentials (ERP) methods were used and recordings were grouped by time from migraine attacks (i.e. "Interictal day", "24 h Before Migraine", "Migraine day" and "Post Migraine"). RESULTS: Twenty-four patients (22 women) recorded an average of 13.3 ± 1.9 days and had 2 ± 0.9 attacks. Twenty-four hours before attack onset, there was a statistically significant modulation of relative power in the delta (decrease) and beta (increase) frequency bands, at rest, and a significant reduction of the amplitude and inter-trial coherence measures of an attention event-related brain potential (P300). CONCLUSIONS: This proof-of-concept study shows that brain state monitoring, utilising an easy-to-use wearable EEG system to track neural modulations at home, can identify physiological changes preceding a migraine attack enabling valuable pre-symptom prediction and subsequent early intervention.

Medical device active surveillance of spontaneous reports: A literature review of signal detection methods.

PURPOSE: The collection and analysis of real-world data for the active monitoring of medical device performance and safety has become increasingly important. Spontaneous reports, such as those in the Food & Drug Administration's (FDA's) Manufacturer and User Facility Device Experience (MAUDE), provide early warning of potential issues with marketed devices. This review synthesizes the current literature on medical device surveillance signal detection and provides a framework for application of methods to active surveillance of spontaneous reports. METHODS: Ovid MEDLINE, Ovid Embase, Scopus, and PubMed databases were systematically searched up to January 2019. Additionally, five methods articles from pharmacovigilance were added that had potential applications to medical devices. RESULTS: Among 105 articles included, the most common source of data (84%) was registries; median time between data collection and publication was 8 years. Surgical procedure outcome signal detection articles comprised 83% while 14% were on device outcome signal detection. The most common family of methods cited (70%) was Sequential Probability Ratio. CONCLUSION: Application of any signal detection algorithm requires careful consideration of influential factors, data limitations, and algorithmic assumptions. We recommend approaches using disproportionality, statistical process control, and sequential probability tests and provide R packages to further development efforts. The small number of published examples suggest that further development of statistical methods and technological solutions to analyze large amounts of data for device safety and performance is needed. Fundamental differences in products, data infrastructure, and the regulatory landscape suggest that medical device vigilance requires its own body of research distinct from pharmacovigilance.

Multi-Cell LTE-U/Wi-Fi Coexistence Evaluation Using a Reinforcement Learning Framework.

Cellular broadband Internet of Things (IoT) applications are expected to keep growing year-by-year, generating demands from high throughput services. Since some of these applications are deployed over licensed mobile networks, as long term evolution (LTE), one already common problem is faced: the scarcity of licensed spectrum to cope with the increasing demand for data rate. The LTE-Unlicensed (LTE-U) forum, aiming to tackle this problem, proposed LTE-U to operate in the 5 GHz unlicensed spectrum. However, Wi-Fi is already the consolidated technology operating in this portion of the spectrum, besides the fact that new technologies for unlicensed band need mechanisms to promote fair coexistence with the legacy ones. In this work, we extend the literature by analyzing a multi-cell LTE-U/Wi-Fi coexistence scenario, with a high interference profile and data rates targeting a cellular broadband IoT deployment. Then, we propose a centralized, coordinated reinforcement learning framework to improve LTE-U/Wi-Fi aggregate data rates. The added value of the proposed solution is assessed by a ns-3 simulator, showing improvements not only in the overall system data rate but also in average user data rate, even with the high interference of a multi-cell environment.

Leveraging LoRaWAN Technology for Precision Agriculture in Greenhouses.

The technology development in wireless sensor network (WSN) offers a sustainable solution towards precision agriculture (PA) in greenhouses. It helps to effectively use the agricultural resources and management tools and monitors different parameters to attain better quality yield and production. WSN makes use of Low-Power Wide-Area Networks (LPWANs), a wireless technology to transmit data over long distances with minimal power consumption. LoRaWAN is one of the most successful LPWAN technologies despite its low data rate and because of its low deployment and management costs. Greenhouses are susceptible to different types of interference and diversification, demanding an improved WSN design scheme. In this paper, we contemplate the viable challenges for PA in greenhouses and propose the successive steps essential for effectual WSN deployment and facilitation. We performed a real-time, end-to-end deployment of a LoRaWAN-based sensor network in a greenhouse of the 'Proefcentrum Hoogstraten' research center in Belgium. We have designed a dashboard for better visualization and analysis of the data, analyzed the power consumption for the LoRaWAN communication, and tried three different enclosure types (commercial, simple box and airflow box, respectively). We validated the implications of real-word challenges on the end-to-end deployment and air circulation for the correct sensor readings. We found that temperature and humidity have a larger impact on the sensor readings inside the greenhouse than we initially thought, which we successfully solved through the airflow box design.

An Ingenious Design of a High Performance-Low Complexity Image Compressor for Wireless Capsule Endoscopy.

Wireless Capsule Endoscopy is a state-of-the-art technology for medical diagnoses of gastrointestinal diseases. The amount of data produced by an endoscopic capsule camera is huge. These vast amounts of data are not practical to be saved internally due to power consumption and the available size. So, this data must be transmitted wirelessly outside the human body for further processing. The data should be compressed and transmitted efficiently in the domain of power consumption. In this paper, a new approach in the design and implementation of a low complexity, multiplier-less compression algorithm is proposed. Statistical analysis of capsule endoscopy images improved the performance of traditional lossless techniques, like Huffman coding and DPCM coding. Furthermore the Huffman implementation based on simple logic gates and without the use of memory tables increases more the speed and reduce the power consumption of the proposed system. Further analysis and comparison with existing state-of-the-art methods proved that the proposed method has better performance.

Redefining Spinal Cord Stimulation "Trials": A Randomized Controlled Trial Using Single-Stage Wireless Permanent Implantable Devices.

BACKGROUND: "Traditional" spinal cord stimulation (SCS) trials with percutaneous electrodes externalized to a pulse generator (PG) are typically limited in duration due to risk of infection. Newer miniaturized wireless SCS technology eliminates the percutaneous extension (as well as PGs implanted for chronic use), thus facilitating a single-stage implantation after which the device can remain indefinitely. OBJECTIVE: To evaluate fully implanted wireless SCS devices during a 30-day screening trial in subjects with chronic low back pain and leg pain and a history of lumbosacral spine surgery. METHODS: In a randomized controlled trial of single-stage wireless SCS using a wireless percutaneous system, 99 subjects received either 10 kHz high frequency stimulation (HFS) or lower frequency stimulation (LFS) below 1500 Hz (Bolash R, Creamer M, Rauck R, et al. Wireless high frequency spinal cord stimulation (10 kHz) compared to multi-waveform low frequency spinal cord stimulation in the management of chronic pain in failed back surgery syndrome subjects: preliminary results of a multicenter, prospective, randomized controlled study. Pain Med 2019, https://doi.org/10.1093/pm/pnz019). In this report, we assess the 30-day trial success rate (≥50% pain relief from baseline) and complications. RESULTS: The overall trial success rate was 88% (87/99): 92% (46/50) for HFS and 84% (41/49) for LFS (NS). The trial success rate in the 64 subjects with predominant low back pain was 92% (59/64) vs. 80% (28/35) in those with leg pain ≥ low back pain (NS). During the screening trial, one infection occurred (1%) and one subject withdrew and was explanted (1%). Electrode migrations were seen on routine follow-up x-rays in 10 cases (10%). CONCLUSION: Using wireless SCS devices that allow for an extended trial period and evaluation of various waveforms, we observed a high rate trial success rate with both HFS and LFS waveforms, with minimal incidence of infection. Long-term follow-up will address the cost-effectiveness and morbidity associated with this technology, which facilitates single-stage treatment.

Comparative analysis of computer-vision and BLE technology based indoor navigation systems for people with visual impairments.

BACKGROUND: Considerable number of indoor navigation systems has been proposed to augment people with visual impairments (VI) about their surroundings. These systems leverage several technologies, such as computer-vision, Bluetooth low energy (BLE), and other techniques to estimate the position of a user in indoor areas. Computer-vision based systems use several techniques including matching pictures, classifying captured images, recognizing visual objects or visual markers. BLE based system utilizes BLE beacons attached in the indoor areas as the source of the radio frequency signal to localize the position of the user. METHODS: In this paper, we examine the performance and usability of two computer-vision based systems and BLE-based system. The first system is computer-vision based system, called CamNav that uses a trained deep learning model to recognize locations, and the second system, called QRNav, that utilizes visual markers (QR codes) to determine locations. A field test with 10 blindfolded users has been conducted while using the three navigation systems. RESULTS: The obtained results from navigation experiment and feedback from blindfolded users show that QRNav and CamNav system is more efficient than BLE based system in terms of accuracy and usability. The error occurred in BLE based application is more than 30% compared to computer vision based systems including CamNav and QRNav. CONCLUSIONS: The developed navigation systems are able to provide reliable assistance for the participants during real time experiments. Some of the participants took minimal external assistance while moving through the junctions in the corridor areas. Computer vision technology demonstrated its superiority over BLE technology in assistive systems for people with visual impairments.

Evolving Spinal Cord Stimulation Technologies and Clinical Implications in Chronic Pain Management.

PURPOSE OF REVIEW: Spinal cord stimulation (SCS), based on the gate theory of nociception, has been shown to be effective in the management of chronic pain conditions. While early-generation technology offered many patients improvement in their pain and symptoms, limitations including paresthesia, dependence on mapping, decreased chronological efficacy, and inadequate coverage left many patients with persistent pain and overt therapeutic failure. RECENT FINDINGS: New advances in neuromodulation technology circumvent many of these previous limitations and offer patients improved pain relief and quality of life. In this review, an update on recent technological developments in the field of SCS and peripheral neuromodulation is presented with discussion on differentiating characteristics which may help guide applicability to individual patient needs.

Towards successful digital transformation through co-creation: a longitudinal study of a four-year implementation of digital monitoring technology in residential care for persons with dementia.

BACKGROUND: Implementation of digital monitoring technology systems is considered beneficial for increasing the safety and quality of care for residents in nursing homes and simultaneously improving care providers' workflow. Co-creation is a suitable approach for developing and implementing digital technologies and transforming the service accordingly. This study aimed to identify the facilitators and barriers for implementation of digital monitoring technology in residential care for persons with dementia and wandering behaviour, and explore co-creation as an implementation strategy and practice. METHODS: In this longitudinal case study, we observed and elicited the experiences of care providers and healthcare managers in eight nursing homes, in addition to those of the information technology (IT) support services and technology vendors, during a four-year implementation process. We were guided by theories on innovation, implementation and learning, as well as co-creation and design. The data were analysed deductively using a determinants of innovation framework, followed by an inductive content analysis of interview and observation data. RESULTS: The implementation represented radical innovation and required far more resources than the incremental changes anticipated by the participants. Five categories of facilitators and barriers were identified, including several subcategories for each category: 1) Pre-implementation preparations; 2) Implementation strategy; 3) Technology stability and usability; 4) Building competence and organisational learning; and 5) Service transformation and quality management. The combination of IT infrastructure instability and the reluctance of the IT support service to contribute in co-creating value with the healthcare services was the most persistent barrier. Overall, the co-creation methodology was the most prominent facilitator, resulting in a safer night monitoring service. CONCLUSION: Successful implementation of novel digital monitoring technologies in the care service is a complex and time-consuming process and even more so when the technology allows care providers to radically transform clinical practices at the point of care, which offers new affordances in the co-creation of value with their residents. From a long-term perspective, the digital transformation of municipal healthcare services requires more advanced IT competence to be integrated directly into the management and provision of healthcare and value co-creation with service users and their relatives.

A Survey on LPWAN Technologies in WBAN for Remote Health-Care Monitoring.

In ubiquitous health-care monitoring (HCM), wireless body area networks (WBANs) are envisioned as appealing solutions that may offer reliable methods for real-time monitoring of patients' health conditions by employing the emerging communication technologies. This paper therefore focuses more on the state-of-the-art wireless communication systems that can be explored in the next-generation WBAN solutions for HCM. Also, this study addressed the critical issues confronted by the existing WBANs that are employed in HCM. Examples of such issues include wide-range health data communication constraint, health data delivery reliability concern, and energy efficiency, which are attributed to the limitations of the legacy short range, medium range, and the cellular technologies that are typically employed in WBAN systems. Since the WBAN sensor devices are usually configured with a finite battery power, they often get drained during prolonged operations. This phenomenon is technically exacerbated by the fact that the legacy communication systems, such as ZigBee, Bluetooth, 6LoWPAN, and so on, consume more energy during data communications. This unfortunate situation offers a scope for employing suitable communication systems identified in this study to improve the productivity of WBANs in HCM. For this to be achieved, the emerging communication systems such as the low-power wide-area networks (LPWANs) are investigated in this study based on their power transmission, data transmission rate, data reliability in the context of efficient data delivery, communication coverage, and latency, including their advantages, as well as disadvantages. As a consequence, the LPWAN solutions are presented for WBAN systems in remote HCM. Furthermore, this research work also points out future directions for the realization of the next-generation of WBANs, as well as how to improve the identified communication systems, to further enhance their productivity in WBAN solutions for HCM.

Recent Progress in Wireless Sensors for Wearable Electronics.

The development of wearable electronics has emphasized user-comfort, convenience, security, and improved medical functionality. Several previous research studies transformed various types of sensors into a wearable form to more closely monitor body signals and enable real-time, continuous sensing. In order to realize these wearable sensing platforms, it is essential to integrate wireless power supplies and data communication systems with the wearable sensors. This review article discusses recent progress in wireless technologies and various types of wearable sensors. Also, state-of-the-art research related to the application of wearable sensor systems with wireless functionality is discussed, including electronic skin, smart contact lenses, neural interfaces, and retinal prostheses. Current challenges and prospects of wireless sensor systems are discussed.

Understanding Probabilistic Cognitive Relaying Communication with Experimental Implementation and Performance Analysis.

Efficiently use of the limited wireless spectrum can be achieved by cooperative cognitive relaying, where secondary users (SUs), who do not pay for the licensed spectrum and have better channel condition to the primary users (PUs) destination, can help the PU by relaying their traffic. A systematic approach of implementing a Cooperative Cognitive Relaying framework using USRP2 is proposed in this paper, which could be used for practical experiments on cognitive radio applications. Two probabilities are introduced in the experiment in the paper and their effect on the PU and SU performance are studied and analyzed. The two probabilities are: (1) Probability of Admission, which controls the PU data that would be allowed by SU in their PU data queue (which could be relayed by SU later) and (2) Probability of Scheduling, which controls the selection of queue at the SU (PU relay data queue or the SU data queue) and the data of the selected queue would be relayed by SU during an idle time slot. Finally, the practical results from the varying of the introduced probabilities on the performance of PU and SU are verified with the simulation results. A very interesting result is found from the practical experiment where it is seen that increasing probability of scheduling of the PU packets at the SU is always in favor of the SU as opposed to the PU in terms of both throughput and delay.

Validity of Wearable Sensors at the Shoulder Joint: Combining Wireless Electromyography Sensors and Inertial Measurement Units to Perform Physical Workplace Assessments.

Background: Workplace adaptation is the preferred method of intervention to diminish risk factors associated with the development of work-related shoulder disorders. However, the majority of the workplace assessments performed are subjective (e.g., questionnaires). Quantitative assessments are required to support workplace adaptations. The aims of this study are to assess the concurrent validity of inertial measurement units (IMUs; MVN, Xsens) in comparison to a motion capture system (Vicon) during lifting tasks, and establish the discriminative validity of a wireless electromyography (EMG) system for the evaluation of muscle activity. Methods: Sixteen participants performed 12 simple tasks (shoulder flexion, abduction, scaption) and 16 complex lifting tasks (lifting crates of different weights at different heights). A Delsys Trigno EMG system was used to record anterior and middle deltoids' EMG activity, while the Xsens and Vicon simultaneously recorded shoulder kinematics. Results: For IMUs, correlation coefficients were high (simple task: >0.968; complex task: >0.84) and RMSEs were low (simple task: <6.72°; complex task: <11.5°). For EMG, a significant effect of weight, height and a weight x height interaction (anterior: p < 0.001; middle: p < 0.03) were observed for RMS EMG activity. Conclusions: These results suggest that wireless EMG and IMUs are valid units that can be used to measure physical demand in workplace assessments.

A Secure Mutual Batch Authentication Scheme for Patient Data Privacy Preserving in WBAN.

The current advances in cloud-based services have significantly enhanced individual satisfaction in numerous modern life areas. Particularly, the recent spectacular innovations in the wireless body area networks (WBAN) domain have made e-Care services rise as a promising application field, which definitely improves the quality of the medical system. However, the forwarded data from the limited connectivity range of WBAN via a smart device (e.g., smartphone) to the application provider (AP) should be secured from an unapproved access and alteration (attacker) that could prompt catastrophic consequences. Therefore, several schemes have been proposed to guarantee data integrity and privacy during their transmission between the client/controller (C) and the AP. Thereby, numerous effective cryptosystem solutions based on a bilinear pairing approach are available in the literature to address the mentioned security issues. Unfortunately, the related solution presents security shortcomings, where AP can with ease impersonate a given C. Hence, this existing scheme cannot fully guarantee C's data privacy and integrity. Therefore, we propose our contribution to address this data security issue (impersonation) through a secured and efficient remote batch authentication scheme that genuinely ascertains the identity of C and AP. Practically, the proposed cryptosystem is based on an efficient combination of elliptical curve cryptography (ECC) and bilinear pairing schemes. Furthermore, our proposed solution reduces the communication and computational costs by providing an efficient data aggregation and batch authentication for limited device's resources in WBAN. These additional features (data aggregation and batch authentication) are the core improvements of our scheme that have great merit for limited energy environments like WBAN.

Internet of Things in Marine Environment Monitoring: A Review.

Marine environment monitoring has attracted more and more attention due to the growing concern about climate change. During the past couple of decades, advanced information and communication technologies have been applied to the development of various marine environment monitoring systems. Among others, the Internet of Things (IoT) has been playing an important role in this area. This paper presents a review of the application of the Internet of Things in the field of marine environment monitoring. New technologies including advanced Big Data analytics and their applications in this area are briefly reviewed. It also discusses key research challenges and opportunities in this area, including the potential application of IoT and Big Data in marine environment protection.

Future of Smart Cardiovascular Implants.

Cardiovascular disease remains the leading cause of death in Western society. Recent technological advances have opened the opportunity of developing new and innovative smart stent devices that have advanced electrical properties that can improve diagnosis and even treatment of previously intractable conditions, such as central line access failure, atherosclerosis and reporting on vascular grafts for renal dialysis. Here we review the latest advances in the field of cardiovascular medical implants, providing a broad overview of the application of their use in the context of cardiovascular disease rather than an in-depth analysis of the current state of the art. We cover their powering, communication and the challenges faced in their fabrication. We focus specifically on those devices required to maintain vascular access such as ones used to treat arterial disease, a major source of heart attacks and strokes. We look forward to advances in these technologies in the future and their implementation to improve the human condition.

A Survey on Wireless Body Area Networks for eHealthcare Systems in Residential Environments.

Current progress in wearable and implanted health monitoring technologies has strong potential to alter the future of healthcare services by enabling ubiquitous monitoring of patients. A typical health monitoring system consists of a network of wearable or implanted sensors that constantly monitor physiological parameters. Collected data are relayed using existing wireless communication protocols to a base station for additional processing. This article provides researchers with information to compare the existing low-power communication technologies that can potentially support the rapid development and deployment of WBAN systems, and mainly focuses on remote monitoring of elderly or chronically ill patients in residential environments.