Epidemiological exploration of the impact of bluetooth headset usage on thyroid nodules using Shapley additive explanations method.

With an increasing prevalence of thyroid nodules globally, this study investigates the potential correlation between the use of Bluetooth headsets and the incidence of thyroid nodules, considering the cumulative effects of non-ionizing radiation (NIR) emitted by these devices. In this study, we analyzed 600 valid questionnaires from the WenJuanXing platform using Propensity Score Matching (PSM) and the XGBOOST model, supplemented by SHAP analysis, to assess the risk of thyroid nodules. PSM was utilized to balance baseline characteristic differences, thereby reducing bias. The XGBOOST model was then employed to predict risk factors, with model efficacy measured by the area under the Receiver Operating Characteristic (ROC) curve (AUC). SHAP analysis helped quantify and explain the impact of each feature on the prediction outcomes, identifying key risk factors. Initially, 600 valid questionnaires from the WenJuanXing platform underwent PSM processing, resulting in a matched dataset of 96 cases for modeling analysis. The AUC value of the XGBOOST model reached 0.95, demonstrating high accuracy in differentiating thyroid nodule risks. SHAP analysis revealed age and daily Bluetooth headset usage duration as the two most significant factors affecting thyroid nodule risk. Specifically, longer daily usage durations of Bluetooth headsets were strongly linked to an increased risk of developing thyroid nodules, as indicated by the SHAP analysis outcomes. Our study highlighted a significant impact relationship between prolonged Bluetooth headset use and increased thyroid nodule risk, emphasizing the importance of considering health impacts in the use of modern technology, especially for devices like Bluetooth headsets that are frequently used daily. Through precise model predictions and variable importance analysis, our research provides a scientific basis for the formulation of public health policies and personal health habit choices, suggesting that attention should be paid to the duration of Bluetooth headset use in daily life to reduce the potential risk of thyroid nodules. Future research should further investigate the biological mechanisms of this relationship and consider additional potential influencing factors to offer more comprehensive health guidance and preventive measures.

Detecting and Understanding Social Influence During Drinking Situations: Protocol for a Bluetooth-Based Sensor Feasibility and Acceptability Study.

BACKGROUND: High-risk alcohol consumption among young adults frequently occurs in the presence of peers who are also drinking. A high-risk drinking situation may consist of particular social network members who have a primary association with drinking. Fine-grained approaches such as ecological momentary assessment (EMA) are growing in popularity for studying real-time social influence, but studies using these approaches exclusively rely on participant self-report. Passive indicators of peer presence using Bluetooth-based technology to detect real-time interactions have the potential to assist in the development of just-in-time interventions. OBJECTIVE: This study seeks to examine the feasibility and acceptability of using a Bluetooth-based sensor and smartphone app to measure social contact in real-world drinking situations. METHODS: Young adults (N=20) who drink heavily and report social drinking will be recruited from the community to participate in a 3-week EMA study. Using a social network interview, index participants will identify and recruit 3 of their friends to carry a Bluetooth beacon. Participants will complete a series of EMA reports on their own personal Android devices including random reports; morning reports; first-drink reports; and signal-contingent reports, which are triggered following the detection of a beacon carried by a peer participant. EMA will assess alcohol use and characteristics of the social environment, including who is nearby and who is drinking. For items about peer proximity and peer drinking, a customized peer list will be presented to participants. Feedback about the study protocol will be ascertained through weekly contact with both index and peer participants, followed by a qualitative interview at the end of the study. We will examine the feasibility and acceptability of recruitment, enrollment of participants and peers, and retention. Feasibility will be determined using indexes of eligibility, enrollment, and recruitment. Acceptability will be determined through participant enrollment and retention, protocol compliance, and participant-reported measures of acceptability. Feasibility and acceptability for peer participants will be informed by enrollment rates, latency to enrollment, compliance with carrying the beacon, and self-reported reasons for compliance or noncompliance with beacon procedures. Finally, EMA data about peer proximity and peer drinking will support the validity of the peer selection process. RESULTS: Participant recruitment began in February 2023, and enrollment was completed in December 2023. Results will be reported in 2025. CONCLUSIONS: The protocol allows us to examine the feasibility and acceptability of a Bluetooth-based sensor for the detection of social contact between index participants and their friends, including social interactions during real-world drinking situations. Data from this study will inform just-in-time adaptive interventions seeking to address drinking in the natural environment by providing personalized feedback about a high-risk social context and alerting an individual that they are in a potentially unsafe situation. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50650.

Remote monitoring of cardiac implantable electronic devices using smart device interface versus radiofrequency-based interface: A systematic review.

Background: Guidelines recommended remote monitoring (RM) in managing patients with Cardiac Implantable Electronic Devices. In recent years, smart device (phone or tablet) monitoring-based RM (SM-RM) was introduced. This study aims to systematically review SM-RM versus bedside monitor RM (BM-RM) using radiofrequency in terms of compliance, connectivity, and episode transmission time. Methods: We conducted a systematic review, searching three international databases from inception until July 2023 for studies comparing SM-RM (intervention group) versus BM-RM (control group). Results: Two matched studies (21 978 patients) were retrieved (SM-RM arm: 9642 patients, BM-RM arm: 12 336 patients). There is significantly higher compliance among SM-RM patients compared with BM-RM patients in both pacemaker and defibrillator patients. Manyam et al. found that more SM-RM patients than BM-RM patients transmitted at least once (98.1% vs. 94.3%, p < .001), and Tarakji et al. showed that SM-RM patients have higher success rates of scheduled transmissions than traditional BM-RM methods (SM-RM: 94.6%, pacemaker manual: 56.3%, pacemaker wireless: 77.0%, defibrillator wireless: 87.1%). There were higher enrolment rates, completed scheduled and patient-initiated transmissions, shorter episode transmission time, and higher connectivity among SM-RM patients compared to BM-RM patients. Younger patients (aged <75) had more patient-initiated transmissions, and a higher proportion had ≥10 transmissions compared with older patients (aged ≥75) in both SM-RM and BM-RM groups. Conclusion: SM-RM is a step in the right direction, with good compliance, connectivity, and shorter episode transmission time, empowering patients to be in control of their health. Further research on cost-effectiveness and long-term clinical outcomes can be carried out.

Exploring the Acceptability and Feasibility of Remote Blood Pressure Measurements and Cognition Assessments Among Participants Recruited From a Safety-Net Emergency Department (Reach Out Cognition): Nonrandomized Mobile Health Trial.

BACKGROUND: Hypertension is a prevalent cardiovascular risk factor disproportionately affecting Black Americans, who also experience a higher incidence of Alzheimer disease and Alzheimer disease-related dementias. Monitoring blood pressure (BP) and cognition may be important strategies in reducing these disparities. OBJECTIVE: The objective of the Reach Out Cognition study was to explore the feasibility and acceptability of remote cognitive and BP assessments in a predominantly Black, low-income population. METHODS: Reach Out was a randomized, controlled, mobile health-based clinical trial to reduce BP among patients with hypertension at an emergency department in a safety-net hospital (ie, a US hospital in which 25% of the patients are Medicaid recipients). Upon conclusion of Reach Out, participants were given the option of continuing into an extension phase, Reach Out Cognition, that included Bluetooth-enabled BP monitoring and digital cognitive assessments for 6 months. Digital cognitive assessments were text message-linked online surveys of the Self-Administered Gerocognitive Exam and Quality of Life in Neurological Disorders scale. BP assessments were measured with Bluetooth-enabled BP cuffs paired with an app and the data were manually sent to the research team. Outcomes were feasibility (ie, enrollment and 3- and 6-month completion of digital cognitive and BP assessments) and acceptability of assessments using a 4-item validated survey, ranging from 1 (not acceptable) to 5 (completely acceptable). RESULTS: Of the 211 Reach Out participants, 107 (50.7%) consented and 71 (33.6%) completed enrollment in Reach Out Cognition. Participants had a mean age of 49.9 years; 70.4% were female and 57.8% identified as Black. Among the 71 participants, 51 (72%) completed cognitive assessments at 3 months and 34 (48%) completed these assessments at 6 months. BP assessments were completed by 37 (52%) and 20 (28%) of the 71 participants at 3 and 6 months, respectively. Participants were neutral on the acceptability of the digital cognitive assessments (mean 3.7) and Bluetooth self-measured BP (SMBP) monitoring (mean 3.9). Participants noted challenges syncing the BP cuff to the app, internet connection, and transmitting the data to the research team. CONCLUSIONS: Enrollment and assessment completion were low, while acceptability was moderate. Technological advances will eliminate some of the Bluetooth SMBP barriers and offer new strategies for cognitive assessments. Subsequent studies could benefit from offering more comprehensive support to overcome Bluetooth-related hurdles, such as personalized training materials, video conferencing, or in-person research team support. Alternatively, strategies that do not require pairing with an app and passive transmission of data could be considered. Overall, further research is warranted to optimize participant engagement and overcome technological challenges. TRIAL REGISTRATION: ClinicalTrials.gov NCT03422718; https://clinicaltrials.gov/study/NCT03422718.

Simplified Indoor Localization Using Bluetooth Beacons and Received Signal Strength Fingerprinting with Smartwatch.

Variations in Global Positioning Systems (GPSs) have been used for tracking users' locations. However, when location tracking is needed for an indoor space, such as a house or building, then an alternative means of precise position tracking may be required because GPS signals can be severely attenuated or completely blocked. In our approach to indoor positioning, we developed an indoor localization system that minimizes the amount of effort and cost needed by the end user to put the system to use. This indoor localization system detects the user's room-level location within a house or indoor space in which the system has been installed. We combine the use of Bluetooth Low Energy beacons and a smartwatch Bluetooth scanner to determine which room the user is located in. Our system has been developed specifically to create a low-complexity localization system using the Nearest Neighbor algorithm and a moving average filter to improve results. We evaluated our system across a household under two different operating conditions: first, using three rooms in the house, and then using five rooms. The system was able to achieve an overall accuracy of 85.9% when testing in three rooms and 92.106% across five rooms. Accuracy also varied by region, with most of the regions performing above 96% accuracy, and most false-positive incidents occurring within transitory areas between regions. By reducing the amount of processing used by our approach, the end-user is able to use other applications and services on the smartwatch concurrently.

A Bluetooth-Based Smartphone App for Detecting Peer Proximity: Protocol for Evaluating Functionality and Validity.

BACKGROUND: While ecological momentary assessment (EMA) is commonly used to study social contexts and social influence in the real world, EMA almost exclusively relies on participant self-report of present circumstances, including the proximity to influential peers. There is the potential for developing a proximity sensing approach that uses small Bluetooth beacons and smartphone-based detection and data collection to collect information about interactions between individuals passively in real time. OBJECTIVE: This paper aims to describe the methods for evaluating the functionality and validity of a Bluetooth-based beacon and a smartphone app to identify when ≥2 individuals are physically proximal. METHODS: We will recruit 20 participants aged 18 to 29 years with Android smartphones to complete a 3-week study during which beacon detection and self-report data will be collected using a smartphone app (MEI Research). Using an interviewer-administered social network interview, participants will identify up to 3 peers of the same age who are influential on health behavior (alcohol use in this study). These peers will be asked to carry a Bluetooth beacon (Kontakt asset tag) for the duration of the study; each beacon has a unique ID that, when detected, will be recorded by the app on the participant's phone. Participants will be prompted to respond to EMA surveys (signal-contingent reports) when a peer beacon encounter meets our criteria and randomly 3 times daily (random reports) and every morning (morning reports) to collect information about the presence of peers. In all reports, the individualized list of peers will be presented to participants, followed by questions about peer and participant behavior, including alcohol use. Data from multiple app data sets, including beacon encounter specifications, notification, and app logs, participant EMA self-reports and postparticipation interviews, and peer surveys, will be used to evaluate project goals. We will examine the functionality of the technology, including the stability of the app (eg, app crashes and issues opening the app), beacon-to-app detection (ie, does the app detect proximal beacons?), and beacon encounter notification when encounter criteria are met. The validity of the technology will be defined as the concordance between passive detection of peers via beacon-to-app communication and the participant's EMA report of peer presence. Disagreement between the beacon and self-report data (ie, false negatives and false positives) will be investigated in multiple ways (ie, to determine if the reason was technology-related or participant compliance-related) using encounter data and information collected from participants and peers. RESULTS: Participant recruitment began in February 2023, and enrollment was completed in December 2023. Results will be reported in 2025. CONCLUSIONS: This Bluetooth-based technology has important applications and clinical implications for various health behaviors, including the potential for just-in-time adaptive interventions that target high-risk behavior in real time. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50241.

An evaluation of the COVID-19 self-service digital contact tracing system in New Zealand.

BACKGROUND: Digital contact tracing (DCT) aims to improve time-to-isolation (timeliness) and find more potentially exposed individuals (sensitivity) to enhance the utility of contact tracing. The aim of this study was to evaluate the public uptake of a DCT self-service survey and its integration with the Bluetooth exposure notification system within the New Zealand Covid Tracer App (NZCTA). METHODS: We adopted a retrospective cohort study design using community COVID-19 cases from February 2022 to August 2022 in New Zealand (1.2 million cases). We examined the proportion of cases completing a self-service survey and the time to complete the survey by age, sex and ethnicity. RESULTS: Overall, 66 % of cases completed their self-service survey. Completion was influenced by age, sex and ethnicity. The median completion time was 1.8 h (IQR 0.2, 17.2), with 95 % of those completing this survey doing so within 48 h of case identification. Around 13 % of all survey completers also uploaded their Bluetooth data, which resulted in an average of 663 cases per day notifying 4.5 contacts per case. CONCLUSION: The combination of high public uptake and rapid response times suggest self-service DCT could be a useful tool for future outbreaks, particularly if implemented in conjunction with manual processes and other DCT tools (e.g. Bluetooth) to address issues related to performance (sensitivity, timeliness), effectiveness, and health equity.

Tracking real-time proximity in daily life: A new tool to examine social interactions.

Social interactions, spending time together, and relationships are important for individuals' well-being, with people feeling happier when they spend more time with others. So far, most information about the frequency and duration of spending time together is based on self-report questionnaires. Although recent technological innovations have stimulated the development of objective approaches for measuring physical proximity in humans in everyday life, these methods still have substantial limitations. Here we present a novel method, using Bluetooth low-energy beacons and a smartphone application, to measure the frequency and duration of dyads being in close proximity in daily life. This method can also be used to link the frequency and duration of proximity to the quality of interactions, by using proximity-triggered questionnaires. We examined the use of this novel method by exploring proximity patterns of family interactions among 233 participants (77 Dutch families, with 77 adolescents [Mage = 15.9] and 145 parents [Mage = 48.9]) for 14 consecutive days. Overall, proximity-based analyses indicated that adolescents were more often and longer in proximity to mothers than to fathers, with large differences between families in frequency and duration. Proximity-triggered evaluations of the interactions and parenting behavior were generally positive for both fathers and mothers. This innovative method is a promising tool that can be broadly used in other social contexts to yield new and more detailed insights into social proximity in daily life.

From wires to waves, a novel sensor system for in vivo pressure monitoring.

Pressure monitoring in various organs of the body is essential for appropriate diagnostic and therapeutic purposes. In almost all situations, monitoring is performed in a hospital setting. Technological advances not only promise to improve clinical pressure monitoring systems, but also engage toward the development of fully implantable systems in ambulatory patients. Such systems would not only provide longitudinal time monitoring to healthcare personnel, but also to the patient who could adjust their way-of-life in response to the measurements. In the past years, we have developed a new type of piezoresistive pressure sensor system. Different bench tests have demonstrated that it delivers precise and reliable pressure measurements in real-time. The potential of this system was confirmed by a continuous recording in a patient that lasted for almost a day. In the present study, we further characterized the functionality of this sensor system by conducting in vivo implantation experiments in nine female farm pigs. To get a step closer to a fully implantable system, we also adapted two different wireless communication solutions to the sensor system. The communication protocols are based on MICS (Medical Implant Communication System) and BLE (Bluetooth Low Energy) communication. As a proof-of-concept, implantation experiments in nine female pigs demonstrated the functionality of both systems, with a notable technical superiority of the BLE.

Low-Power and Wireless Communication Research on Underground Displacement Three-Dimensional Monitoring System.

Underground displacement monitoring is a crucial means of preventing geological disasters. Compared to existing one-dimensional methods (measuring only horizontal or vertical displacement), the underground displacement three-dimensional measurement method and monitoring system proposed by the author's research team can more accurately reflect the internal movement of rock and soil mass, thereby improving the timeliness and accuracy of geological disaster prediction. To ensure the reliability and long-term operation of the underground displacement three-dimensional monitoring system, this article further introduces low-power design theory and Bluetooth wireless transmission technology into the system. By optimizing the power consumption of each sensing unit, the current during the sleep period of a single sensing unit is reduced to only 0.09 mA. Dynamic power management technology is employed to minimize power consumption during each detection cycle. By using Bluetooth wireless transmission technology, the original wired communication of the system is upgraded to a relay-type wireless network communication, effectively solving the problem of the entire sensing array's operation being affected when a single sensing unit is damaged. These optimized designs not only maintain monitoring accuracy (horizontal and vertical displacement errors not exceeding 1 mm) but also enable the monitoring system to operate stably for an extended period under harsh weather conditions.

A 2.4 GHz Wide-Range CMOS Current-Mode Class-D PA with HD2 Suppression for Internet of Things Applications.

Short-range Internet of Things (IoT) sensor nodes operating at 2.4 GHz must provide ubiquitous wireless sensor networks (WSNs) with energy-efficient, wide-range output power (POUT). They must also be fully integrated on a single chip for wireless body area networks (WBANs) and wireless personal area networks (WPANs) using low-power Bluetooth (BLE) and Zigbee standards. The proposed fully integrated transmitter (TX) utilizes a digitally controllable current-mode class-D (CMCD) power amplifier (PA) with a second harmonic distortion (HD2) suppression to reduce VCO pulling in an integrated system while meeting harmonic limit regulations. The CMCD PA is divided into 7-bit slices that can be reconfigured between differential and single-ended topologies. Duty cycle distortion compensation is performed for HD2 suppression, and an HD2 rejection filter and a modified C-L-C low-pass filter (LPF) reduce HD2 further. Implemented in a 28 nm CMOS process, the TX achieves a wide POUT range of from 12.1 to -31 dBm and provides a maximum efficiency of 39.8% while consuming 41.1 mW at 12.1 dBm POUT. The calibrated HD2 level is -82.2 dBc at 9.93 dBm POUT, resulting in a transmitter figure of merit (TX_FoM) of -97.52 dB. Higher-order harmonic levels remain below -41.2 dBm even at 12.1 dBm POUT, meeting regulatory requirements.

Bluetooth dataset for proximity detection in indoor environments collected with smartphones.

This paper describes a data collection experiment and the resulting dataset based on Bluetooth beacon messages collected in an indoor museum. The goal of this dataset is to study algorithms and techniques for proximity detection between people and points of interest (POI). To this purpose, we release the data we collected during 32 museum's visits, in which we vary the adopted smartphones and the visiting paths. The smartphone is used to collect Bluetooth beacons emitted by Bluetooth tags positioned nearby each POI. The visiting layout defines the order of visit of 10 artworks. The combination of different smartphones, the visiting paths and features of the indoor museum allow experiencing with realistic environmental conditions. The dataset comprises RSS (Received Signal Strength) values, timestamp and artwork identifiers, as long as a detailed ground truth, reporting the starting and ending time of each artwork's visit. The dataset is addressed to researchers and industrial players interested in further investigating how to automatically detect the location or the proximity between people and specific points of interest, by exploiting commercial technologies available with smartphone. The dataset is designed to speed up the prototyping process, by releasing an accurate ground truth annotation and details concerning the adopted hardware.

Different Scenarios of Autonomous Operation of an Environmental Sensor Node Using a Piezoelectric-Vibration-Based Energy Harvester.

This paper delves into the application of vibration-based energy harvesting to power environmental sensor nodes, a critical component of modern data collection systems. These sensor nodes play a crucial role in structural health monitoring, providing essential data on external conditions that can affect the health and performance of structures. We investigate the feasibility and efficiency of utilizing piezoelectric vibration energy harvesters to sustainably power environmental wireless sensor nodes on the one hand. On the other hand, we exploit different approaches to minimize the sensor node's power consumption and maximize its efficiency. The investigations consider various sensor node platforms and assess their performance under different voltage levels and broadcast frequencies. The findings reveal that optimized harvester designs enable real-time data broadcasting with short intervals, ranging from 1 to 3 s, expanding the horizons of environmental monitoring, and show that in case the system includes a battery as a backup plan, the battery's lifetime can be extended up to 9 times. This work underscores the potential of vibration energy harvesting as a viable solution for powering sensor nodes, enhancing their autonomy, and reducing maintenance costs in remote and challenging environments. It opens doors to broader applications of sustainable energy sources in environmental monitoring and data collection systems.

A Circular, Wireless Surface-Electromyography Array.

Commercial, high-tech upper limb prostheses offer a lot of functionality and are equipped with high-grade control mechanisms. However, they are relatively expensive and are not accessible to the majority of amputees. Therefore, more affordable, accessible, open-source, and 3D-printable alternatives are being developed. A commonly proposed approach to control these prostheses is to use bio-potentials generated by skeletal muscles, which can be measured using surface electromyography (sEMG). However, this control mechanism either lacks accuracy when a single sEMG sensor is used or involves the use of wires to connect to an array of multiple nodes, which hinders patients' movements. In order to mitigate these issues, we have developed a circular, wireless s-EMG array that is able to collect sEMG potentials on an array of electrodes that can be spread (not) uniformly around the circumference of a patient's arm. The modular sEMG system is combined with a Bluetooth Low Energy System on Chip, motion sensors, and a battery. We have benchmarked this system with a commercial, wired, state-of-the-art alternative and found an r = 0.98 (p < 0.01) Spearman correlation between the root-mean-squared (RMS) amplitude of sEMG measurements measured by both devices for the same set of 20 reference gestures, demonstrating that the system is accurate in measuring sEMG. Additionally, we have demonstrated that the RMS amplitudes of sEMG measurements between the different nodes within the array are uncorrelated, indicating that they contain independent information that can be used for higher accuracy in gesture recognition. We show this by training a random forest classifier that can distinguish between 6 gestures with an accuracy of 97%. This work is important for a large and growing group of amputees whose quality of life could be improved using this technology.

A Holistic Approach for Enhancing Museum Performance and Visitor Experience.

Managing modern museum content and visitor data analytics to achieve higher levels of visitor experience and overall museum performance is a complex and multidimensional issue involving several scientific aspects, such as exhibits' metadata management, visitor movement tracking and modelling, location/context-aware content provision, etc. In related prior research, most of the efforts have focused individually on some of these aspects and do not provide holistic approaches enhancing both museum performance and visitor experience. This paper proposes an integrated conceptualisation for improving these two aspects, involving four technological components. First, the adoption and parameterisation of four ontologies for the digital documentation and presentation of exhibits and their conservation methods, spatial management, and evaluation. Second, a tool for capturing visitor movement in near real-time, both anonymously (default) and eponymously (upon visitor consent). Third, a mobile application delivers personalised content to eponymous visitors based on static (e.g., demographic) and dynamic (e.g., visitor movement) data. Lastly, a platform assists museum administrators in managing visitor statistics and evaluating exhibits, collections, and routes based on visitors' behaviour and interactions. Preliminary results from a pilot implementation of this holistic approach in a multi-space high-traffic museum (MELTOPENLAB project) indicate that a cost-efficient, fully functional solution is feasible, and achieving an optimal trade-off between technical performance and cost efficiency is possible for museum administrators seeking unfragmented approaches that add value to their cultural heritage organisations.

BLE-Based Indoor Localization: Analysis of Some Solutions for Performance Improvement.

This paper addresses indoor localization using an anchor-based system based on Bluetooth Low Energy (BLE) 5.0 technology, adopting the Received Signal Strength Indicator (RSSI) for the distance estimation. Different solutions have been proposed in the scientific literature to improve the performance of this localization technology, but a detailed performance comparison of these solutions is still missing. The aim of this work is to make an experimental analysis combining different solutions for the performance improvement of BLE-based indoor localization, identifying the most effective one. The considered solutions involve different RSSI signals' conditioning, the use of anchor-tag distance estimation techniques, as well as approaches for estimating the unknown tag position. An experimental campaign was executed in a complex indoor environment, characterized by the continuous presence in the movement of working staff and numerous obstacles. The exploitation of multichannel transmission using RSSI signal aggregation techniques showed the greater performance improvement of the localization system, reducing the positioning error (from 1.5 m to about 1 m). The other examined solutions have shown a lesser impact in the performance improvement with a decrease or an increase in the positioning errors, depending on the considered combination of the adopted solutions.

Bluetooth Tactical Headsets Improve The Speed of Accurate Patient Handoffs.

BACKGROUND: The Committee on En Route Combat Casualty Care recently ranked the patient handoff as their fourth research priority. Bluetooth technology has been introduced to the battlefield and has the potential to improve the tactical patient handoff. The purpose of this study is to compare the traditional methods of communication used in tactical medical evacuation by Special Operations medical personnel (radio push-to-talk [PTT] and Tactical Medic Intercom System [TM-ICS]) to Bluetooth communication. METHODS: Twenty-four simulated tactical patient handoffs were performed to compare Bluetooth and traditional methods of communication used in tactical medical evacuation. Patient scenario order and method of communication were randomized. Accuracy and time required to complete the patient handoff were determined. The study took place using a rotary-wing aircraft kept at level 2 to simulate real-world background noise. Preferred method of communication for each study participant was determined. RESULTS: There were no differences in accuracy of the received patient handoffs between groups or patient handoff transmission times at the ramp of the aircraft. However, when comparing patient handoff times to the medical team within the aircraft, Bluetooth communication was significantly faster than both TM-ICS and radio PTT, while Bluetooth PTT and radio PTT were also significantly faster than TM-ICS. Bluetooth communication was ranked as the preferred method of handoff by all study participants. CONCLUSION: The study demonstrated that utilization of Bluetooth technology for patient handover results in faster handoffs compared with traditional methods without sacrificing any accuracy in a scenario with high levels of noise.

Graph Trilateration for Indoor Localization in Sparsely Distributed Edge Computing Devices in Complex Environments Using Bluetooth Technology.

Spatial navigation patterns in indoor space usage can reveal important cues about the cognitive health of participants. In this work, we present a low-cost, scalable, open-source edge computing system using Bluetooth low energy (BLE) beacons for tracking indoor movements in a large, 1700 m2 facility used to carry out therapeutic activities for participants with mild cognitive impairment (MCI). The facility is instrumented with 39 edge computing systems, along with an on-premise fog server. The participants carry a BLE beacon, in which BLE signals are received and analyzed by the edge computing systems. Edge computing systems are sparsely distributed in the wide, complex indoor space, challenging the standard trilateration technique for localizing subjects, which assumes a dense installation of BLE beacons. We propose a graph trilateration approach that considers the temporal density of hits from the BLE beacon to surrounding edge devices to handle the inconsistent coverage of edge devices. This proposed method helps us tackle the varying signal strength, which leads to intermittent detection of beacons. The proposed method can pinpoint the positions of multiple participants with an average error of 4.4 m and over 85% accuracy in region-level localization across the entire study area. Our experimental results, evaluated in a clinical environment, suggest that an ordinary medical facility can be transformed into a smart space that enables automatic assessment of individuals' movements, which may reflect health status or response to treatment.

Direct Bluetooth connectivity results in better hearing aid compliance in children.

OBJECTIVE: To determine if hearing aid use in school aged children is impacted when upgraded to direct Bluetooth® enabled technology. We hypothesized that because children are better able to connect to their devices and headphones, they would be more inclined to use their hearing aids throughout the day, resulting in an increase in hearing aid compliance. METHODS: This retrospective analysis examined changes in datalogging of hours of usage per day in 51 school aged children who underwent an upgrade from non-direct Bluetooth® hearing technology to direct Bluetooth®-enabled hearing technology. RESULTS: Hours per day of hearing aid use in all hearing aid users significantly increased after upgrading to DBT enabled technology (6.82 vs 9.82, <0.001). There were no significant differences noted in hours before and after upgrade depending on race (p = 0.147), gender (p = 0.887), developmental delay (p = 0.749), type of hearing loss (p = 0.218), and degree of hearing loss (p = 0.551). However, when comparing private versus Medicaid insurance, there was noted to be a significant difference with the odds of an increase in hours of usage after upgrade being higher for those patients privately insured (OR = 1.247, p < 0.001, 95 % CI 1.093-1.422). CONCLUSION: Direct Bluetooth® enabled hearing technology positively impacts children's hearing aid compliance, which has the potential improve speech and language outcomes.

Introducing a New Mobile Electroencephalography System and Evaluating Its Quality in Comparison to Clinical Electroencephalography.

Electroencephalography (EEG) is a crucial tool in cognitive neuroscience, enabling the study of neurophysiological function by measuring the brain's electrical activity. Its applications include perception, learning, memory, language, decision making and neural network mapping. Recently, interest has surged in extending EEG measurements to domestic environments. However, the high costs associated with traditional laboratory EEG systems have hindered accessibility for many individuals and researchers in education, research, and medicine. To tackle this, a mobile-EEG device named "DreamMachine" was developed. A more affordable alternative to both lab-based EEG systems and existing mobile-EEG devices. This system boasts 24 channels, 24-bit resolution, up to 6 h of battery life, portability, and a low price. Our open-source and open-hardware approach empowers cognitive neuroscience, especially in education, learning, and research, opening doors to more accessibility. This paper introduces the DreamMachine's design and compares it with the lab-based EEG system "asalabTM" in an eyes-open and eyes-closed experiment. The Alpha band exhibited higher power in the power spectrum during eyes-closed conditions, whereas the eyes-open condition showed increased power specifically within the Delta frequency range. Our analysis confirms that the DreamMachine accurately records brain activity, meeting the necessary standards when compared to the asalabTM system.