Personal Glucose Meter for α-Glucosidase Inhibitor Screening Based on the Hydrolysis of Maltose.

As a key enzyme regulating postprandial blood glucose, α-Glucosidase is considered to be an effective target for the treatment of diabetes mellitus. In this study, a simple, rapid, and effective method for enzyme inhibitors screening assay was established based on α-glucosidase catalyzes reactions in a personal glucose meter (PGM). α-glucosidase catalyzes the hydrolysis of maltose to produce glucose, which triggers the reduction of ferricyanide (K3[Fe(CN)6]) to ferrocyanide (K4[Fe(CN)6]) and generates the PGM detectable signals. When the α-glucosidase inhibitor (such as acarbose) is added, the yield of glucose and the readout of PGM decreased accordingly. This method can achieve the direct determination of α-glucosidase activity by the PGM as simple as the blood glucose tests. Under the optimal experimental conditions, the developed method was applied to evaluate the inhibitory activity of thirty-four small-molecule compounds and eighteen medicinal plants extracts on α-glucosidase. The results exhibit that lithospermic acid (52.5 ± 3.0%) and protocatechualdehyde (36.8 ± 2.8%) have higher inhibitory activity than that of positive control acarbose (31.5 ± 2.5%) at the same final concentration of 5.0 mM. Besides, the lemon extract has a good inhibitory effect on α-glucosidase with a percentage of inhibition of 43.3 ± 3.5%. Finally, the binding sites and modes of four active small-molecule compounds to α-glucosidase were investigated by molecular docking analysis. These results indicate that the PGM method is feasible to screening inhibitors from natural products with simple and rapid operations.

Responsive Neurostimulation as a Novel Palliative Option in Epilepsy Surgery.

Patients with drug-resistant focal onset epilepsy are not always suitable candidates for resective surgery, a definitive intervention to control their seizures. The alternative surgical treatment for these patients in Japan has been vagus nerve stimulation (VNS). Besides VNS, epileptologists in the United States can choose a novel palliative option called responsive neurostimulation (RNS), a closed-loop neuromodulation system approved by the US Food and Drug Administration in 2013. The RNS System continuously monitors neural electroencephalography (EEG) activity at the possible seizure onset zone (SOZ) where electrodes are placed and responds with electrical stimulation when a pre-defined epileptic activity is detected. The controlled clinical trials in the United States have demonstrated long-term utility and safety of the RNS System. Seizure reduction rates have continued to improve over time, reaching 75% over 9 years of treatment. The incidence of implant-site infection, the most frequent device-related adverse event, is similar to those of other neuromodulation devices. The RNS System has shown favorable efficacy for both mesial temporal lobe epilepsy (TLE) and neocortical epilepsy of the eloquent cortex. Another unique advantage of the RNS System is its ability to provide chronic monitoring of ambulatory electrocorticography (ECoG). Valuable information obtained from ECoG monitoring provides a better understanding of the state of epilepsy in each patient and improves clinical management. This article reviews the developmental history, structure, and clinical utility of the RNS System, and discusses its indications as a novel palliative option for drug-resistant epilepsy.

Enabling Remote Patient Monitoring Through the Use of Smart Thermostat Data in Canada: Exploratory Study.

BACKGROUND: Advances in technology have made the development of remote patient monitoring possible in recent years. However, there is still room for innovation in the types of technologies that are developed, used, and implemented. The smart thermostat solutions provided in this study can expand beyond typically defined features and be used for improved holistic health monitoring purposes. OBJECTIVE: The aim of this study is to validate the hypothesis that remote motion sensors could be used to quantify and track an individual's movements around the house. On the basis of our results, the next step would be to determine if using remote motion sensors could be a novel data collection method compared with the national census-level surveys administered by governmental bodies. The results will be used to inform a more extensive implementation study of similar smart home technologies to gather data for machine learning algorithms and to build upon pattern recognition and comprehensive health monitoring. METHODS: We conducted a pilot study with a sample size of 8 to validate the use of remote motion sensors to quantify movement in the house. A large database containing data from smart home thermostats was analyzed to compare the following indicators; sleep, physical activity, and sedentary behavior. These indicators were developed by the Public Health Agency of Canada and are collected through traditional survey methods. RESULTS: The results showed a significant Spearman rank correlation coefficient of 0.8 (P<.001), which indicates a positive linear association between the total number of sensors activated and the total number of indoor steps traveled by study participants. In addition, the indicators of sleep, physical activity, and sedentary behavior were all found to be highly comparable with those attained by the Public Health Agency of Canada. CONCLUSIONS: The findings demonstrate that remote motion sensors data from a smart thermostat solution are a viable option when compared with traditional survey data collection methods for health data collection and are also a form of zero-effort technology that can be used to monitor the activity levels and nature of activity of occupants within the home.

Design of the Pregnancy REmote MOnitoring II study (PREMOM II): a multicenter, randomized controlled trial of remote monitoring for gestational hypertensive disorders.

BACKGROUND: Observational data from the retrospective, non-randomized Pregnancy REmote MOnitoring I (PREMOM I) study showed that remote monitoring (RM) may be beneficial for prenatal observation of women at risk for gestational hypertensive disorders (GHD) in terms of clinical outcomes, health economics, and stakeholder perceptions. PREMOM II is a prospective, randomized, multicenter follow-up study that was performed to explore these promising results. METHODS: After providing written consent, 3922 pregnant women aged ≥18 years who are at increased risk of developing GHD will be randomized (1:1:1 ratio) to (a) conventional care (control group), (b) a patient self-monitoring group, and (c) a midwife-assisted RM group. The women in each group will be further divided (1:1 ratio) to evaluate the outcomes of targeted or non-targeted (conventional) antihypertensive medication. Women will be recruited in five hospitals in Flanders, Belgium: Ziekenhuis Oost-Limburg, Universitaire Ziekenhuis Antwerpen, Universitaire Ziekenhuis Leuven, AZ Sint Jan Brugge-Oostende, and AZ Sint Lucas Brugge. The primary outcomes are: (1) numbers and types of prenatal visits; (2) maternal outcomes; (3) neonatal outcomes; (4) the applicability and performance of RM; and (5) compliance with RM and self-monitoring. The secondary outcomes are: (1) cost-effectiveness and willingness to pay; (2) patient-reported outcome measures (PROMS) questionnaires on the experiences of the participants; and (3) the maternal and perinatal outcomes according to the type of antihypertensive medication. Demographic, and maternal and neonatal outcomes are collected from the patients' electronic records. Blood pressure and compliance rate will be obtained from an online digital coordination platform for remote data handling. Information about the healthcare-related costs will be obtained from the National Coordination Committee of Belgian Health Insurance Companies (Intermutualistisch Agentschap). PROMS will be assessed using validated questionnaires. DISCUSSION: To our knowledge, this is the first randomized trial comparing midwife-assisted RM and self-monitoring of prenatal blood pressure versus conventional management among women at increased risk of GHD. Positive results of this study may lead to a practical framework for caregivers, hospital management, and payers to introduce RM into the prenatal care programs of high-risk pregnancies. TRIAL REGISTRATION: This study was registered on clinicaltrials.gov , identification number NCT04031430. Registered 24 July 2019, https://clinicaltrials.gov/ct2/show/NCT04031430?cond=premom+ii&draw=2&rank=1 .

A new era in electroencephalographic monitoring? Subscalp devices for ultra-long-term recordings.

Inaccurate subjective seizure counting poses treatment and diagnostic challenges and thus suboptimal quality in epilepsy management. The limitations of existing hospital- and home-based monitoring solutions are motivating the development of minimally invasive, subscalp, implantable electroencephalography (EEG) systems with accompanying cloud-based software. This new generation of ultra-long-term brain monitoring systems is setting expectations for a sea change in the field of clinical epilepsy. From definitive diagnoses and reliable seizure logs to treatment optimization and presurgical seizure foci localization, the clinical need for continuous monitoring of brain electrophysiological activity in epilepsy patients is evident. This paper presents the converging solutions developed independently by researchers and organizations working at the forefront of next generation EEG monitoring. The immediate value of these devices is discussed as well as the potential drivers and hurdles to adoption. Additionally, this paper discusses what the expected value of ultra-long-term EEG data might be in the future with respect to alarms for especially focal seizures, seizure forecasting, and treatment personalization.

Effect of novel technology-enabled multidimensional physical activity feedback in primary care patients at risk of chronic disease - the MIPACT study: a randomised controlled trial.

BACKGROUND: Technological progress has enabled the provision of personalised feedback across multiple dimensions of physical activity that are important for health. Whether this multidimensional approach supports physical activity behaviour change has not yet been examined. Our objective was to examine the effectiveness of a novel digital system and app that provided multidimensional physical activity feedback combined with health trainer support in primary care patients identified as at risk of chronic disease. METHODS: MIPACT was a parallel-group, randomised controlled trial that recruited patients at medium (≥10 and < 20%) or high (≥20%) risk of cardiovascular disease and/or type II diabetes from six primary care practices in the United Kingdom. Intervention group participants (n = 120) received personal multidimensional physical activity feedback using a customised digital system and web-app for 3 months plus five health trainer-led sessions. All participants received standardised information regarding physical activity. Control group participants (n = 84) received no further intervention. The primary outcome was device-based assessment of physical activity at 12 months. RESULTS: Mean intervention effects were: moderate-vigorous physical activity: -1.1 (95% CI, - 17.9 to 15.7) min/day; moderate-vigorous physical activity in ≥10-min bouts: 0.2 (- 14.2 to 14.6) min/day; Physical Activity Level (PAL): 0.00 (- 0.036 to 0.054); vigorous physical activity: 1.8 (- 0.8 to 4.2) min/day; and sedentary time: 10 (- 19.3 to 39.3) min/day. For all of these outcomes, the results showed that the groups were practically equivalent and statistically ruled out meaningful positive or negative effects (>minimum clinically important difference, MCID). However, there was profound physical activity multidimensionality, and only a small proportion (5%) of patients had consistently low physical activity across all dimensions. CONCLUSION: In patients at risk of cardiovascular disease and/or type II diabetes, MIPACT did not increase mean physical activity. Using a sophisticated multidimensional digital approach revealed enormous heterogeneity in baseline physical activity in primary care patients, and practitioners may need to screen for low physical activity across dimensions rather than rely on disease-risk algorithms that are heavily influenced by age. TRIAL REGISTRATION: This trial is registered with the ISRCTN registry ( ISRCTN18008011 ; registration date 31 July 2013).

Autonomic nervous system changes detected with peripheral sensors in the setting of epileptic seizures.

A better understanding of the early detection of seizures is highly desirable as identification of an impending seizure may afford improved treatments, such as antiepileptic drug chronotherapy, or timely warning to patients. While epileptic seizures are known to often manifest also with autonomic nervous system (ANS) changes, it is not clear whether ANS markers, if recorded from a wearable device, are also informative about an impending seizure with statistically significant sensitivity and specificity. Using statistical testing with seizure surrogate data and a unique dataset of continuously recorded multi-day wristband data including electrodermal activity (EDA), temperature (TEMP) and heart rate (HR) from 66 people with epilepsy (9.9 ± 5.8 years; 27 females; 161 seizures) we investigated differences between inter- and preictal periods in terms of mean, variance, and entropy of these signals. We found that signal mean and variance do not differentiate between inter- and preictal periods in a statistically meaningful way. EDA signal entropy was found to be increased prior to seizures in a small subset of patients. Findings may provide novel insights into the pathophysiology of epileptic seizures with respect to ANS function, and, while further validation and investigation of potential causes of the observed changes are needed, indicate that epilepsy-related state changes may be detectable using peripheral wearable devices. Detection of such changes with wearable devices may be more feasible for everyday monitoring than utilizing an electroencephalogram.

Evaluating the Impact of Freespira on Panic Disorder Patients' Health Outcomes and Healthcare Costs within the Allegheny Health Network.

Panic disorder (PD) is a debilitating condition that drives medical spending at least twice as high as medically matched controls. Excessive utilization of healthcare resources comes from emergency department (ED), medications, diagnostic testing, and physician visits. Freespira is an FDA-cleared digital therapeutic that treats PD and panic attacks (PA) by correcting underlying abnormal respiratory physiology. Efficacy of Freespira has been established in prior studies. This paper reports on a quality improvement program that investigated whether treating PD patients with Freespira would reduce medical costs and improve outcomes over 12-months. Panic symptoms were assessed using the Panic Disorder Severity Scale (PDSS). Pre-and post-treatment insurance claims determined costs. At baseline, mean Clinician Global Impression (CGI-S) was 4.4 (moderately/markedly ill), mean PDSS was 14.4 and mean PA frequency/week was 2 (range 0-5). Immediately post-treatment (week 5) mean CGI-S, PDSS and weekly PA frequency declined to 2.8 (borderline/mildly ill, 4.9 (remission) and 0.2 (range 0-2) respectively, p < 0.001. 82% reported PDSS decrease of ≥ 40% (clinically significant), 86% were PA-free. One-year post treatment mean CGI-S, PDSS and PA remained low at 2.1, 4.4, and 0.3 (range 0-1) respectively. 91% had PDSS decrease of ≥ 40%, 73% were PA-free. The majority of patients were panic attack free and/or reduced their symptoms and avoidance behaviors 1-year post Freespira treatment. Mean overall medical costs were reduced by 35% from $548 to $358 PMPM (per member per month) or an annual reduction of $2280. at 12 months post-treatment. There was a 65% reduction in ED costs from $87 to $30 PMPM. Median pharmacy costs were reduced by 68% from $73 to $23 PMPM.

Prediction using a randomized evaluation of data collection integrated through connected technologies (PREDICT): Design and rationale of a randomized trial of patients discharged from the hospital to home.

BACKGROUND: Hospital readmission prediction models often perform poorly. A critical limitation is that they use data collected up until the time of discharge but do not leverage information on patient behaviors at home after discharge. METHODS: PREDICT is a two-arm, randomized trial comparing ways to use remotely-monitored patient activity levels after hospital discharge to improve hospital readmission prediction models. Patients are randomly assigned to use a wearable device or smartphone application to track physical activity data. The study collects also validated assessments on patient characteristics as well as disparate data on credit scores and medication adherence. Patients are followed for 6 months. We evaluate whether these data sources can improve prediction compared to standard modelling approaches. CONCLUSION: The PREDICT Trial tests a novel method of remotely-monitoring patient behaviors after hospital discharge. Findings from the trial could inform new ways to improve the identification of patients at high-risk for hospital readmission. TRIAL REGISTRATION: Clinicaltrials.gov Identifier: NCT02983812.

Accessibility and feasibility of using technology to support mindfulness practice, reduce stress and promote long term mental health.

BACKGROUND AND PURPOSE: We evaluated the feasibility of using an activity monitor to support mindfulness practice, reduce self-reported stress and physiological indicators of stress. MATERIALS AND METHODS: Adult women (N = 19) who previously participated in a mindfulness intervention wore an activity monitor for eight-weeks. The activity monitor notified them when they were stressed (based on standard deviation pulse pressure). Heart rate and pulse pressure were continuously collected via the activity monitor. Mindfulness, stress, depression and trauma symptoms were collected via self-report surveys. RESULTS: There were no significant changes in self-reported stress, depression, post-traumatic stress and mindfulness from baseline to eight-weeks. Pulse pressure and standard deviation of pulse pressure increased over time. Those who were high on the non-judge mindfulness subscale had a lower standard deviation pulse pressure and spent less time stressed. CONCLUSION: Those who are more mindful are less likely to have physiological signs of stress.

Ambulatory Versus Laboratory Polysomnography in Obstructive Sleep Apnea: Comparative Assessment of Quality, Clinical Efficacy, Treatment Compliance, and Quality of Life.

STUDY OBJECTIVES: This study has as its primary objective to evaluate the quality and effectiveness of type II ambulatory polysomnography (Amb-PSG) versus type I attended laboratory polysomnography (Lab-PSG) in diagnosing obstructive sleep apnea (OSA). Its secondary objective is to evaluate the clinical efficacy, quality of life (QoL), and treatment adherence after diagnosis. METHODS: An observational study of patients with OSA (n = 225) in whom diagnosis was made via Amb-PSG (n = 114) or Lab-PSG (n = 111). Patients' clinical data were retrospectively assessed (including general demographic and clinical data, Epworth Sleepiness Scale, blood pressure, indices from polysomnography, and treatment adherence. Cross-sectional assessment (patient questionnaire) was used to evaluate clinical efficacy indicators, comorbidities, current treatment, and QoL. RESULTS: Polysomnography indices were comparable between Amb-PSG and Lab-PSG (apnea-hypopnea index: 38.9 ± 22.5 versus 35.8 ± 23.1 events/h; P > .05), except for an elevation of total sleep time (510 ± 54.7 versus 476.3 ± 79.4 minutes; P < .01) and loss of oximetry signal (9.8% versus 0.0%; P < .05). Based on polysomnography parameters, OSA was severe in 119 patients (52.9%), moderate in 88 (39.1%), and mild in 18 (8.0%). Diagnostic effect of Amb-PSG in clinical (body mass index, blood pressure, Epworth Sleepiness Scale) and treatment follow-up (CPAP adherence and QoL) indicators was comparable to that of Lab-PSG. CONCLUSIONS: Amb-PSG showed an OSA diagnostic capacity comparable to Lab-PSG. Secondary analyses (diagnostic quality, clinical efficacy, treatment compliance, QoL) underline the value of Amb-PSG as an emerging alternative to improve accessibility to care.

A sensor-based wrist pulse signal processing and lung cancer recognition.

Pulse diagnosis is an efficient method in traditional Chinese medicine for detecting the health status of a person in a non-invasive and convenient way. Jin's pulse diagnosis (JPD) is a very efficient recent development that is gradually recognized and well validated by the medical community in recent years. However, no acceptable results have been achieved for lung cancer recognition in the field of biomedical signal processing using JPD. More so, there is no standard JPD pulse feature defined with respect to pulse signals. Our work is designed mainly for care giving service conveniently at home to the people having lung cancer by proposing a novel wrist pulse signal processing method, having an insight from JPD. We developed an iterative slide window (ISW) algorithm to segment the de-noised signal into single periods. We analyzed the characteristics of the segmented pulse waveform and for the first time summarized 26 features to classify the pulse waveforms of healthy individuals and lung cancer patients using a cubic support vector machine (CSVM). The result achieved by the proposed method is found to be 78.13% accurate.

Activities suggestion based on emotions in AAL environments.

The elderly population is increasing and the response of the society was to provide them with services directed to them to cope with their needs. One of the oldest solutions is the retirement home, providing housing and permanent assistance for the elderly. Furthermore, most of the retirement homes are inhabited by multiple elderly people, thus creating a community of people who are somewhat related in age and medical issues. The ambient assisted living (AAL) area tries to solve some of the elderly issues by producing technological products, some of them dedicated to elderly homes. One of the identified problem is that elderly people are sometimes discontent about the activities that consume most of their day promoted by the retirement home social workers. The work presented in this paper attempts to improve how these activities are scheduled taking into account the elderlies' emotional response to these activities. The aim is to maximize the group happiness by promoting the activities the group likes, minding if they are bored due to activities repetition. In this sense, this paper presents an extension of the Cognitive Life Assistant platform incorporating a social emotional model. The proposed system has been modelled as a free time activity manager which is in charge of suggesting activities to the social workers.

Telemonitoring-based feedback improves adherence to non-vitamin K antagonist oral anticoagulants intake in patients with atrial fibrillation.

Aims: To evaluate the effect of telemonitoring on adherence to non-vitamin K antagonist oral anticoagulants (NOACs) in atrial fibrillation (AF) patients. Methods and results: A randomized, single-blind, crossover, controlled trial in 48 AF patients on once or twice daily (OD or BID) NOAC. The Medication Event Monitoring System tracked NOAC intake during three phases of 3 months each: daily telemonitoring, telemonitoring with immediate telephone feedback in case of intake errors, and an observation phase without daily transmissions. Unprotected days were defined as ≥ 3 or ≥ 1 consecutively missed doses for a BID or OD NOAC, respectively, or excess dose intake. Cost-effectiveness was calculated based on anticipated stroke reduction derived from patients' risk profile and measured intake. Persistence over the entire study was 98%. Telemonitoring-only already led to very high taking and regimen adherence (97.4% respectively 93.8%). Nevertheless, direct feedback further improved both to 99.0% and 96.8%, respectively (P < 0.001 respectively P = 0.002). Observation without daily monitoring resulted in a significant waning of taking adherence (94.3%; P = 0.049). Taking adherence was significantly higher for OD compared to BID NOAC, although unprotected days were similar. Feedback intervention had an incremental cost of €344 289 to prevent one stroke, but this could be as low as €15 488 in high-risk patients with low adherence and optimized technology. Conclusion: Telemonitoring resulted in high NOAC adherence due to the notion of being watched, as evidenced by the rapid decline during the observation period. Feedback further optimized adherence. Telemonitoring with or without feedback may be a cost-effective approach in high-risk patients deemed poorly adherent.

Assessing the Correlation Between Physical Activity and Quality of Life in Advanced Lung Cancer.

BACKGROUND AND OBJECTIVE: Increasing physical activity (PA) is safe and beneficial in lung cancer (LC) patients. Advanced-stage LC patients are under-studied and have worse symptoms and quality of life (QoL). We evaluated the feasibility of monitoring step count in advanced LC as well as potential correlations between PA and QoL. METHODS: This is a prospective, observational study of 39 consecutive patients with advanced-stage LC. Daily step count over 1 week (via Fitbit Zip), QoL, dyspnea, and depression scores were collected. Spearman rank testing was used to assess correlations. Correlation coefficients (ρ) >0.3 or <-0.3 (more and less correlated, respectively) were considered potentially clinically significant. RESULTS: Most (83%) of the patients were interested in participating, and 67% of those enrolled were adherent with the device. Of those using the device (n = 30), the average daily step count was 4877 (range = 504-12 118) steps/d. Higher average daily step count correlated with higher QoL (ρ = 0.46), physical (ρ = 0.61), role (ρ = 0.48), and emotional functioning (ρ = 0.40) scores as well as lower depression (ρ = -0.40), dyspnea (ρ = -0.54), and pain (ρ = -0.37) scores. CONCLUSION: Remote PA monitoring (Fitbit Zip) is feasible in advanced-stage LC patients. Interest in participating in this PA study was high with comparable adherence to other PA studies. In those utilizing the device, higher step count correlates with higher QoL as well as lower dyspnea, pain, and depression scores. PA monitoring with wearable devices in advanced-stage LC deserves further study.

E-health beyond technology: analyzing the paradigm shift that lies beneath.

Information and computer technology has come to play an increasingly important role in medicine, to the extent that e-health has been described as a disruptive innovation or revolution in healthcare. The attention is very much focused on the technology itself, and advances that have been made in genetics and biology. This leads to the question: What is changing in medicine today concerning e-health? To what degree could these changes be characterized as a 'revolution'? We will apply the work of Thomas Kuhn, Larry Laudan, Michel Foucault and other philosophers-which offers an alternative understanding of progress and revolution in medicine to the classic discovery-oriented approach-to our analysis. Nowadays, the long-standing curative or reactive paradigm in medicine is facing a crisis due to an aging population, a significant increase in chronic diseases and the development of more expensive diagnostic tools and therapies. This promotes the evolution towards a new paradigm with an emphasis on preventive medicine. E-health constitutes an essential part of this new paradigm that seeks to solve the challenges presented by an aging population, skyrocketing costs and so forth. Our approach changes the focus from the technology itself toward the underlying paradigm shift in medicine. We will discuss the relevance of this approach by applying it to the surge in digital self-tracking through health apps and wearables: the recognition of the underlying paradigm shift leads to a more comprehensive understanding of self-tracking than a solely discovery-oriented or technology-focused view can provide.

Personalized Health Monitoring System for Managing Well-Being in Rural Areas.

Rural India lacks easy access to health practitioners and medical centers, depending instead on community health workers. In these areas, common ailments that are easy to manage with medicines, often lead to medical escalations and even fatalities due to lack of awareness and delayed diagnosis. The introduction of wearable health devices has made it easier to monitor health conditions and to connect doctors and patients in urban areas. However, existing initiatives have not succeeded in providing adequate health monitoring to rural and low-literate patients, as current methods are expensive, require consistent connectivity and expect literate users. Our design considerations address these concerns by providing low-cost medical devices connected to a low-cost health platform, along with personalized guidance based on patient physiological parameters in local languages, and alerts to medical practitioners in case of emergencies. This patient-centric integrated healthcare system is designed to manage the overall health of villagers with real-time health monitoring of patients, to offer guidance on preventive care, and to increase health awareness and self-monitoring at an affordable price. This personalized health monitoring system addresses the health-related needs in remote and rural areas by (1) empowering health workers in monitoring of basic health conditions for rural patients in order to prevent escalations, (2) personalized feedback regarding nutrition, exercise, diet, preventive Ayurveda care and yoga postures based on vital parameters and (3) reporting of patient data to the patient's health center with emergency alerts to doctor and patient. The system supports community health workers in the diagnostic procedure, management, and reporting of rural patients, and functions well even with only intermittent access to Internet.

EMOTEO: A Smartphone Application for Monitoring and Reducing Aversive Tension in Borderline Personality Disorder Patients, a Pilot Study.

PURPOSE: We developed a smartphone application (App; EMOTEO: emotion-meteo [weather forecast]) to help borderline personality disorder (BPD) patients to monitor and regulate their inner tension. The App proposes targeted mindfulness-based exercises. DESIGN AND METHODS: We assessed the usability and efficiency of this App for monitoring and reduction of aversive tension in 16 BPD participants over a 6-month period. FINDINGS: We recorded a mean of 318.1 sessions (SD = 166.7) per participants, with a high level of satisfaction. There was a significant decrease in aversive tension (p < .05) and the App was mainly used around 10 a.m. and 9 p.m. PRACTICE IMPLICATIONS: EMOTEO was user-friendly and efficient in reducing aversive tension in BPD patients.