Access to trauma center care: A statewide system-based approach.

BACKGROUND: Timely access to specialized trauma care is a vital element in patient outcome after severe and critical injury requiring the skills of trauma teams in levels I and II trauma centers to avoid preventable mortality. We used system-based models to estimate timely access to care. METHODS: Trauma system models consisted of ground emergency medical services, helicopter emergency medical services, and designated levels I to V trauma centers were constructed for five states. These models incorporated geographic information systems along with traffic data and census block group data to estimate population access to trauma care within the "golden hour." Trauma systems were further analyzed to identify the optimal location for an additional level I or II trauma center that would provide the greatest increase in access. RESULTS: The population of the states studied totaled 23 million people, of which 20 million (87%) had access to a level I or II trauma center within 60 minutes. Statewide-specific access ranged from 60% to 100%. Including levels III to V trauma centers, access within 60 minutes increased to 22 million (96%), ranging from 95% to 100%. The addition of a levels I and II trauma center in an optimized location in each state would provide timely access to a higher trauma capability for an additional 1.1 million, increasing total access to approximately 21.1 million people (92%). CONCLUSION: This analysis demonstrates that nearly universal access to trauma care is present in these states when including levels I to V trauma centers. However, concerning gaps remain in timely access to levels I and II trauma centers. This study provides an approach to determine more robust statewide estimates of access to care. It highlights the need for a national trauma system, one in which all components of state-managed trauma systems are assembled in a national data set to accurately identify gaps in care. LEVEL OF EVIDENCE: Therapeutic/Care Management; Level IV.

Detecting disability using self-reported and clinical assessments in early-stage relapsing-remitting multiple sclerosis: Looking for a complementary approach.

Disability accrual is mainly driven by progression independent of relapse activity, which is present even in early stages of relapsing-remitting multiple sclerosis (RRMS) and sometimes overlooked. This multicenter, non-interventional study evaluated whether patient-reported outcomes measures (PROMs) could capture disability in 189 early-stage RRMS patients (mean age: 36.1 ± 9.4 years, 71.4% female, mean disease duration: 1.4 ± 0.8 years, median EDSS: 1.0). The 9-Hole Peg Test (9-HPT), NeuroQoL Upper Extremity (NeuroQoL-UE), Timed 25-Foot Walk (T25-FW), Multiple Sclerosis Walking Scale (MSWS-12), Symbol Digit Modalities Test (SDMT), and Perceived Deficits Questionnaire (PDQ-5) were used to assess hand function, gait, and cognition, respectively. These functions were at least mildly affected in this early-stage population, finding significant correlations between PROMs and clinical assessments. PROMs could enable early-stage RRMS patients to communicate their perceived disability in different domains, assisting clinicians in disease monitoring and decision making.

Activation and On-Scene Intervals for Severe Trauma EMS Interventions: An Analysis of the NEMSIS Database.

Objective: Time to care is a determinant of trauma patient outcomes, and timely delivery of trauma care to severely injured patients is critical in reducing mortality. Numerous studies have analyzed access to care using prehospital intervals from a Carr et al. meta-analysis of studies from 1975 to 2005. Carr et al.'s research sought to determine national mean activation and on-scene intervals for trauma patients using contemporary emergency medical services (EMS) records. Since the Carr et al. meta-analysis was published, the National Highway Traffic Safety Administration (NHTSA) created and refined the National Emergency Medical Services Information System (NEMSIS) database. We sought to perform a modern analysis of prehospital intervals to establish current standards and temporal patterns.Methods: We utilized NEMSIS to analyze EMS data of trauma patients from 2016 to 2019. The dataset comprises more than 94 million EMS records, which we filtered to select for severe trauma and stratified by type of transport and rurality to calculate mean activation and on-scene intervals. Furthermore, we explored the impact of basic life support (BLS) and advanced life support (ALS) of ground units on activation and on-scene time intervals.Results: Mean activation and on-scene intervals for ground transport were statistically different when stratified by rurality. Urban, suburban, and rural ground activation intervals were 2.60 ± 3.94, 2.88 ± 3.89, and 3.33 ± 4.58 minutes, respectively. On-scene intervals were 15.50 ± 10.46, 17.56 ± 11.27, and 18.07 ± 16.13 minutes, respectively. Mean helicopter transport activation time was 13.75 ± 7.44 minutes and on-scene time was 19.42 ± 16.09 minutes. This analysis provides an empirically defined mean for activation and on-scene times for trauma patients based on transport type and rurality. Results from this analysis proved to be significantly longer than the previous analysis, except for helicopter transport on-scene time. Shorter mean intervals were seen in ALS compared to BLS for activation intervals, however ALS on-scene intervals were marginally longer than BLS.Conclusions: With the increasing sophistication of geospatial technologies employed to analyze access to care, these intervals are the most accurate and up-to-date and should be included in access to care models.

Assessing care-related regret among nurses specialized in multiple sclerosis: A psychometric analysis of a new assessment battery.

Experiences of regret associated with caring for patients with multiple sclerosis (MS) can affect medical decisions. A non-interventional study was conducted to assess the dimensionality and item characteristics of a battery including the Regret Intensity Scale (RIS-10) and 15 items evaluating common situations experienced by nurses in MS care. A total of 97 nurses were included. The RIS-10 showed good internal reliability and a unidimensional structure according to Mokken analysis. All-item homogeneity coefficients exceeded 0.30, whereas scalability for the overall RIS-10 was 0.66, indicating a strong scale. This battery showed adequate psychometric properties to evaluate regret among MS nurses.

Sick leave and occupational burnout among nurses caring for patients with multiple sclerosis.

BACKGROUND: Sick leave is a common problem among healthcare professionals. Nurses play a critical role in the multidisciplinary management of multiple sclerosis (MS). However, limited information is available on the phenomenon of sick leave among MS nurses. OBJECTIVE: The aim of this study was to assess the presence of sick leave among nurses caring for patients with MS and to identify associated factors. METHODS: We conducted a multicenter, non-interventional, cross-sectional, web-based study. Nurses involved in MS care from across Spain answered a survey composed of demographic characteristics, professional background, questions about their standard practice, and a behavioral battery including the Maslach Burnout Inventory - Human Services Survey (MBI-HSS). A multivariable logistic regression analysis was conducted to determine the association between nurses' characteristics and sick leave. RESULTS: Ninety-six nurses were included in the study. Mean age (SD) was 44.6 (9.8) years, and 91.7% were female. Participants had a median of 6 (IQR 3.0, 11.0) years of expertise in MS managing a median of 15 (5.0, 35.0) patients per week. Sixteen participants (16.7%) had been on sick leave in the last 6 months, with a median absence of 14.5 days (7.0, 30.0). Sixteen nurses (16.7%) reported severe burnout. Participants on sick leave had higher levels of emotional exhaustion (mean MBI-HSS scores of 22.3 and 16.0, p=0.01) and inadequate interactions with their colleagues (mean Practice Environment Scale - Nursing Work Index scores of 11.8 and 13.1, p=0.01) than their counterparts. Burnout was associated with higher risk of sick leave in the multivariable analysis (OR=1.06 [95% CI 1.00, 1.13], p=0.04) after adjustment for confounders. CONCLUSIONS: Occupational burnout is associated with increased risk of sick leave among nurses managing patients with MS. Identifying burnout may be critical for implementing specific intervention strategies to maintain an adequate functioning of MS care units.

Preferences Toward Attributes of Disease-Modifying Therapies: The Role of Nurses in Multiple Sclerosis Care.

ABSTRACT: BACKGROUND: Nurses play an essential role in coordinating the care of patients with multiple sclerosis (MS) throughout their disease trajectory in a complex treatment landscape. The aim of this study was to assess nurses' preferences toward different disease-modifying therapy attributes. METHODS: We conducted a multicenter, noninterventional, cross-sectional study in collaboration with the Sociedad Española de Enfermería Neurológica. Nurses actively involved in MS care were invited to participate in the study. Prevention of disability progression, preservation of cognitive function, side effect profile and safety monitoring, and method of administration were the treatment attributes tested. Conjoint analysis was used to assess preferences in 8 simulated treatment options and rank them from most to least preferred. RESULTS: A total of 98 nurses were included in the study. The mean (SD) age was 44.7 (9.8) years, and 91.8% were female with a mean (SD) time of experience in MS care of 7.5 (5.4) years. Participants prioritized preservation of cognition (38.6%), followed by preventing disability progression (35.2%) and side effect risk and safety monitoring (13.5%). Route and frequency of administration were the least preferred attributes (7.4% and 5.3%, respectively). Estimated utilities were consistent across the sample according to sociodemographic and professional practice characteristics. CONCLUSIONS: Nurses' preferences toward treatments were mainly driven by efficacy attributes. This information may support the role of nurses in the multidisciplinary management of MS facilitating shared decision making.

Behavioral aspects of nurse practitioners associated with optimal multiple sclerosis care in Spain.

BACKGROUND: Nurse practitioners (NPs) play a critical role in the multidisciplinary management of patients with multiple sclerosis (MS). Neurologists´ behavioral characteristics have been associated with suboptimal clinical decisions. However, limited information is available on their impact among NPs involved in MS care. The aim of this study was to assess nurses´ therapeutic choices to understand behavioral factors influencing their decision making process. METHODS: A non-interventional, cross-sectional, web-based study was conducted. NPs actively involved in the care of patients with MS were invited to participate in the study by the Spanish Society of Neurology Nursing. Participants answered questions regarding their standard practice and therapeutic management of seven simulated relapsing-remitting MS (RRMS) case scenarios. A behavioral battery was used to measure participants´ life satisfaction, mood, positive social behaviors, feeling of helpfulness, attitudes toward adoption of evidence-based innovations, occupational burnout, and healthcare-related regret. The outcome of interest was therapeutic inertia (TI), defined as the lack of treatment escalation when there is clinical and radiological evidence of disease activity. A score to quantify TI was created based on the number of simulated scenarios where treatment intensification was warranted. RESULTS: Overall, 331 NPs were invited to participate, 130 initiated the study, and 96 (29%) completed the study. The mean age (SD) was 44.6 (9.8) years and 91.7% were female. Seventy-three participants (76.0%) felt their opinions had a significant influence on neurologists´ therapeutic decisions. Sixteen NPs (16.5%) showed severe emotional exhaustion related to work and 13 (13.5%) had depressive symptoms. The mean (SD) TI score was 0.97 (1.1). Fifty-six of NPs showed TI in at least one case scenario. Higher years of nursing experience (p = 0.014), feeling of helpfulness (p = 0.014), positive attitudes toward innovations (p = 0.046), and a higher intensity of care-related regret (p = 0.021) were associated with a lower risk of TI (adjusted R2 = 0.28). Burnout was associated with higher risk of TI (p = 0.001). CONCLUSIONS: Although NPs cannot prescribe MS treatments in Spain, their behavioral characteristics may influence the management of patients with RRMS. Continuing education and specific strategies for reducing occupational burnout may lead to better management skills and improve MS care.

An FPGA-Based Machine Learning Tool for In-Situ Food Quality Tracking Using Sensor Fusion.

The continuous development of more accurate and selective bio- and chemo-sensors has led to a growing use of sensor arrays in different fields, such as health monitoring, cell culture analysis, bio-signals processing, or food quality tracking. The analysis and information extraction from the amount of data provided by these sensor arrays is possible based on Machine Learning techniques applied to sensor fusion. However, most of these computing solutions are implemented on costly and bulky computers, limiting its use in in-situ scenarios outside complex laboratory facilities. This work presents the application of machine learning techniques in food quality assessment using a single Field Programmable Gate Array (FPGA) chip. The characteristics of low-cost, low power consumption as well as low-size allow the application of the proposed solution even in space constrained places, as in food manufacturing chains. As an example, the proposed system is tested on an e-nose developed for beef classification and microbial population prediction.

Short-term data on disease activity, cognition, mood, stigma and employment outcomes in a cohort of patients with primary progressive multiple sclerosis (UPPMS study).

BACKGROUND: Primary progressive multiple sclerosis (PPMS) has long been defined by progressive disability accrual in the absence of initial relapses. However, its underlying neurodegenerative process seems to be accompanied by central nervous system inflammation. A new classification defined multiple sclerosis courses according to clinical/radiological activity and progression. We provide further insight into PPMS activity according to this classification and other daily living aspects. METHODS: This was a multicentre, prospective, cohort study including 55 adult patients with PPMS according to 2010 McDonald criteria, within ten years from neurologic symptom onset and not receiving disease-modifying therapies during the past six months, who were followed up for 12 months. The primary study endpoint was the percentage of patients with active disease based on clinical relapses and/or magnetic resonance activity. Disability progression, cognitive function, physical/psychological impact, depression symptoms, stigma and employment were secondary endpoints. RESULTS: Eleven (25.6%) patients exhibited multiple sclerosis activity throughout the 12-month study follow-up. Fourteen showed non-active multiple sclerosis without progression, 11 non-active multiple sclerosis with progression, 6 active multiple sclerosis without progression and 4 active multiple sclerosis with progression; one patient with disease activity was not assessable for progression. Cognitive function scores remained unchanged or increased, disease physical impact was maintained and disease psychological impact significantly decreased. The proportion of patients with depression symptoms or stigma remained without significant changes as well as employment outcomes. CONCLUSION: This study shows that one-fourth of PPMS patients may exhibit disease activity over one year, with disability progression in approximately one-third but without worsening of cognitive function, disease impact, depression, stigma or employment outcomes.

A Pilot Study to Explore Patient Satisfaction With a Virtual Rehabilitation Program in Multiple Sclerosis: The RehabVR Study Protocol.

Background: Virtual reality (VR) has emerged as a promising treatment approach in rehabilitation for patients with multiple sclerosis (MS) due to its potential to increase patient motivation and rehabilitation adherence. One of the key features for rehabilitation adherence is patient satisfaction with the VR rehabilitation (VRR) program, and information on user satisfaction and not only effectiveness is required to systematically include VRR in routine clinical practice. Given that information on patient satisfaction with VRR is scarce, the primary objective of this study is to assess long-term patient satisfaction with a novel VRR program. This program has been specifically designed for MS patients by a multidisciplinary team of specialists, based on an effective conventional rehabilitation (CR) program. Secondarily, discomfort with VRR will be evaluated, and therapy adherence and changes in a variety of domains typically affected by MS will be compared between patients receiving VRR and patients receiving CR. Methods: In this prospective single-center 6-months follow-up study, 32 and 16 MS patients will receive VRR or CR, respectively. Patients will attend twice weekly rehabilitation sessions on site during 4 weeks, and they will continue with rehabilitation at home for five additional months. Satisfaction, assessed by the User Satisfaction Evaluation Questionnaire (USEQ), at 6 months of the VRR program initiation will be the primary outcome. Secondary outcomes include adherence, disability, spasms and spasticity, balance, fatigue, activities of daily living (ADLs), depression, anxiety, work status, cognition, demographic, and clinical characteristics (in the VRR and CR groups), and discomfort (in the VRR group). Outcome measures will be assessed at baseline, and at 1 and 6 months of rehabilitation initiation. Discussion: The study is intended to provide a better understanding of long-term patient satisfaction with a VRR program specifically designed for MS patients. Additionally, the study will provide information on long-term adherence, changes in motor symptoms, cognitive functions and patient-reported outcomes after the rehabilitation program. The results from this study will help to gather valuable knowledge on the use of rehabilitation with a new VR tool in MS patients.

CSF chitinase 3-like-1 association with disability of primary progressive MS.

OBJECTIVE: To assess the role of CSF chitinase 3-like-1 (CHI3L1), chitinase 3-like-2 (CHI3L2), and neurofilament light chain (NfL) in predicting the course of primary progressive MS (PPMS). METHODS: We analyzed CSF CHI3L1, CHI3L2, and NfL levels in 25 patients with PPMS with disease duration ≤10 years and no disease-modifying therapy for ≥6 months from the prospective Understanding Primary Progressive Multiple Sclerosis cohort study. CSF samples taken at disease diagnosis were analyzed using commercial ELISAs and following the manufacturer's instructions. Data on Expanded Disability Status Scale (EDSS) scores, disability progression, and cognitive function according to the Brief Repeatable Neuropsychological Battery were also assessed throughout the 1-year study follow-up. RESULTS: Increasing CHI3L1 levels correlated with higher EDSS scores at baseline (ρ = 0.490, 95% CI 0.118-0.742, p = 0.013) and month 12 (ρ = 0.455, 95% CI 0.063-0.725, p = 0.026) and tended to be associated with a higher risk of disability progression according to EDSS scores (OR = 1.008, 95% CI 0.999-1.017, p = 0.089). Increasing CHI3L2 levels also tended to correlate with lower baseline EDSS scores (ρ = -0.366, 95% CI -0.676-0.054, p = 0.086). There was no correlation with regard to NfL levels. CONCLUSIONS: This analysis supports the association between CSF CHI3L1 levels and neurologic disability according to EDSS scores in patients with PPMS. Other chitinase-like proteins such as CHI3L2 may also be involved. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that CSF CHI3L1 is associated with neurologic disability in patients with PPMS.

Workplace difficulties, health-related quality of life, and perception of stigma from the perspective of patients with Multiple Sclerosis.

INTRODUCTION: In Multiple Sclerosis (MS), withdrawal from employment is a critical problem. This study explores relationships between disease characteristics, work difficulties, health-related quality of life, depression, and stigma and how these factors affect employment status. METHODS: A multicenter, non-interventional, cross-sectional study was conducted in adults with relapsing-remitting MS (RRMS) and primary progressive MS (PPMS). Patient-reported questionnaires included: 23-item Multiple Sclerosis Work Difficulties Questionnaire, 29-item Multiple Sclerosis Impact Scale, Stigma Scale for Chronic Illness, and Beck Depression Inventory-Fast Screen. RESULTS: A total of 199 individuals (mean age = 43.9 ± 10.5 years, 60.8% female, 86.4% with RRMS) participated in the study. Mean time from diagnosis was 9.6 ± 7.2 years and median Expanded Disability Status Scale score was 2.0 (interquartile range: 1.0-3.5). Employment rate was 47.2% (n = 94). Mean physical and psychological MSIS-29 impact sub-scores were 40.38 ± 17.1 and 20.24 ± 7.8, respectively. Forty patients (19.9%) had at least one SSCI-8 item with a score of 4 or 5, suggesting the presence of stigma often or always. Eighty-one patients (40.7%) were depressed and 25 (12.6%) had moderate-to-severe depression. Work difficulties were higher in those with worse functional status, a diagnosis of PPMS, and lower educational levels. Employed participants had lower perceptions of stigma and depressive symptoms than those not employed. Higher perceptions of stigma were also strongly linked to higher physical and psychological impact on health-related quality of life and greater work difficulties. Depressive symptoms were also strongly related to work-related problems. CONCLUSIONS: Work difficulties, stigma and poor quality of life are common in MS patients, even in a population with low physical disability. Evaluation of these dimensions in clinical practice would allow the development of targeted rehabilitation and specific work plans for MS employers.

A CMOS Low Pass Filter for SoC Lock-in-Based Measurement Devices.

This paper presents a fully integrated Gm-C low pass filter (LPF) based on a current steering Gm reduction-tuning technique, specifically designed to operate as the output stage of a SoC lock-in amplifier. To validate this proposal, a first-order and a second-order single-ended topology were integrated into a 1.8 V to 0.18 µm CMOS (Complementary Metal-Oxide-Semiconductor) process, showing experimentally a tuneable cutoff frequency that spanned five orders of magnitude, from tens of mHz to kHz, with a constant current consumption (below 3 µA/pole), compact size (<0.0140 mm2/pole), and a dynamic range better than 70 dB. Compared to state-of-the-art solutions, the proposed approach exhibited very competitive performances while simultaneously fully satisfying the demanding requirements of on-chip portable measurement systems in terms of highly efficient area and power. This is of special relevance, taking into account the current trend towards multichannel instruments to process sensor arrays, as the total area and power consumption will be proportional to the number of channels.

Correction to: Economic burden of multiple sclerosis in a population with low physical disability.

It has been highlighted that the original article [1] contained a mistake in the 'Results' section, specifically in the percentages of female subjects and those with diagnosis of RRMS. Please note that this mistake has only been present in the 'Results' section, the Abstract and Table 1 remain unchanged. This article shows the incorrect and correct version of the percentages.

Economic burden of multiple sclerosis in a population with low physical disability.

BACKGROUND: In multiple sclerosis (MS), half of affected people are unemployed within 10 years of diagnosis. The aim of this study was to assess the economic impact of MS in adult subjects with relapsing-remitting MS (RRMS) and primary progressive MS (PPMS). METHODS: A multicenter, non-interventional, cross-sectional study was conducted. The Expanded Disability Status Scale (EDSS) and the 23-item Multiple Sclerosis Work Difficulties Questionnaire (MSWDQ-23) were used to assess disability and work performance, respectively. Only indirect costs were considered using the human capital method, including work costs. Professional support costs and informal caregivers' costs were also estimated. RESULTS: A total of 199 subjects were studied (mean age: 43.9 ± 10.5 years, 60.8% female, 86.4% with RRMS). Median EDSS score was 2.0 (interquartile range: 1.0-3.5) and median MSWDQ-23 total score was 31.5 (15.2, 50.0). The number of employed subjects decreased after MS diagnosis from 70.6 to 47.2%, and the number of retired people increased (23.6%). Mean age of retirement was 43.6 ± 10.5 years. Ten percent of the population had sick leaves (absenteeism was seen in 90.9% of the student population and 30.9% of the employed population). Professional support in their daily life activities was needed in 28.1% of subjects. Costs for sick leave, work absenteeism, premature retirement and premature work disability/pensioner were €416.6 ± 2030.2, €763.4 ± 3161.8, €5810.1 ± 13,159.0 and €1816.8 ± 9630.7, respectively. Costs for professional support and informal caregiving activities were €1026.93 ± 4622.0 and €1328.72, respectively. CONCLUSIONS: MS is responsible for a substantial economic burden due to indirect and informal care costs, even in a population with low physical disability.

Multi-Institutional Multidisciplinary Injury Mortality Investigation in the Civilian Pre-Hospital Environment (MIMIC): a methodology for reliably measuring prehospital time and distance to definitive care.

The detailed study of prehospital injury death is critical to advancing trauma and emergency care, as circumstance and causality have significant implications for the development of mitigation strategies. Though there is no true 'Golden Hour,' the time from injury to care is a critical element in the analysis matrix, particularly in patients with severe injury. Currently, there is no standard method for the assessment of time to definitive care after injury among prehospital deaths. This article describes a methodology to estimate total prehospital time and distance for trauma patients transported via ground emergency medical services and helicopter emergency medical services using a geographic information system. Data generated using this method, along with medical examiner and field investigation reports, will be used to estimate the potential survivability of prehospital trauma deaths occurring in five US states and the District of Columbia as part of the Multi-Institutional Multidisciplinary Injury Mortality Investigation in the Civilian Pre-Hospital Environment study. One goal of this work is to develop standard metrics for the assessment of total prehospital time and distance, which can be used in the future for more complex spatial analyses to gain a deeper understanding of trauma center access. Results will be used to identify high priority areas for research and development in injury prevention, trauma system performance improvement, and public health.

A 0.18 µm CMOS LDO Regulator for an On-Chip Sensor Array Impedance Measurement System.

This paper presents a fully integrated 0.18 μm CMOS Low-Dropout (LDO) Voltage Regulator specifically designed to meet the stringent requirements of a battery-operated impedance spectrometry multichannel CMOS micro-instrument. The proposed LDO provides a regulated 1.8 V voltage from a 3.6 V to 1.94 V battery voltage over a −40 °C to 100 °C temperature range, with a compact topology (<0.10 mm² area) and a constant quiescent current of only 7.45 μA with 99.985% current efficiency, achieving remarkable state-of-art Figures of Merit (FoMs) for the regulating⁻transient performance. Experimental measurements validate its suitability for the target application, paving the way towards the future achievement of a truly portable System on Chip (SoC) platform for impedance sensors.

A CMOS Self-Contained Quadrature Signal Generator for SoC Impedance Spectroscopy.

This paper presents a low-power fully integrated quadrature signal generator for system-on-chip (SoC) impedance spectroscopy applications. It has been designed in a 0.18 μm-1.8 V CMOS technology as a self-contained oscillator, without the need for an external reference clock. The frequency can be digitally tuned from 10 to 345 kHz with 12-bit accuracy and a relative mean error below 1.7%, thus supporting a wide range of impedance sensing applications. The proposal is experimentally validated in two impedance spectrometry examples, achieving good magnitude and phase recovery results compared to the results obtained using a commercial LCR-meter. Besides the wide frequency tuning range, the proposed programmable oscillator features a total power consumption lower than 0.77 mW and an active area of 0.129 mm², thus constituting a highly suitable choice as stimulation module for instrument-on-a-chip devices.

A Compact Energy Harvesting System for Outdoor Wireless Sensor Nodes Based on a Low-Cost In Situ Photovoltaic Panel Characterization-Modelling Unit.

This paper presents a low-cost high-efficiency solar energy harvesting system to power outdoor wireless sensor nodes. It is based on a Voltage Open Circuit (VOC) algorithm that estimates the open-circuit voltage by means of a multilayer perceptron neural network model trained using local experimental characterization data, which are acquired through a novel low cost characterization system incorporated into the deployed node. Both units-characterization and modelling-are controlled by the same low-cost microcontroller, providing a complete solution which can be understood as a virtual pilot cell, with identical characteristics to those of the specific small solar cell installed on the sensor node, that besides allows an easy adaptation to changes in the actual environmental conditions, panel aging, etc. Experimental comparison to a classical pilot panel based VOC algorithm show better efficiency under the same tested conditions.

A Wearable Wireless Sensor Network for Indoor Smart Environment Monitoring in Safety Applications.

This paper presents the implementation of a wearable wireless sensor network aimed at monitoring harmful gases in industrial environments. The proposed solution is based on a customized wearable sensor node using a low-power low-rate wireless personal area network (LR-WPAN) communications protocol, which as a first approach measures CO2 concentration, and employs different low power strategies for appropriate energy handling which is essential to achieving long battery life. These wearables nodes are connected to a deployed static network and a web-based application allows data storage, remote control and monitoring of the complete network. Therefore, a complete and versatile remote web application with a locally implemented decision-making system is accomplished, which allows early detection of hazardous situations for exposed workers.