Wearable sensors in healthcare and sensor-enhanced health information systems: all our tomorrows?

Effect of stress-based interventions on the quality of life of people with an intellectual disability and their caregivers

PURPOSE

People with intellectual disabilities often show challenging behaviour, which can manifest itself in self-harm or aggression towards others. Real-time monitoring of stress in clients with challenging behaviour can help caregivers to promptly deploy interventions to prevent escalations, ultimately to improve the quality of life of client and caregiver. This study aimed to assess the impact of real-time stress monitoring with HUME, and the subsequent interventions deployed by the care team, on stress levels and quality of life.

MATERIALS AND METHODS

Real-time stress monitoring was used in 41 clients with intellectual disabilities in a long-term care setting over a period of six months. Stress levels were determined at the start and during the deployment of the stress monitoring system. The quality of life of the client and caregiver was measured with the Outcome Rating Scale at the start and at three months of use.

RESULTS

The results showed that the HUME-based interventions resulted in a stress reduction. The perceived quality of life was higher after three months for both the clients and caregivers. Furthermore, interventions to provide proximity were found to be most effective in reducing stress and increasing the client's quality of life.

CONCLUSIONS

The study demonstrates that real-time stress monitoring with the HUME and the following interventions were effective. There was less stress in clients with an intellectual disability and an increase in the perceived quality of life. Future larger and randomized controlled studies are needed to confirm these findings.

Protein-structure-dependent spectral shifts of near-infrared photoluminescence from locally functionalized single-walled carbon nanotubes based on avidin-biotin interactions

Single-walled carbon nanotubes (SWCNTs) emit photoluminescence (PL) in the near-infrared (NIR) region (>900 nm). To enhance their PL properties, defect doping via local chemical functionalization has been developed. The locally functionalized SWCNTs (lf-SWCNTs) emit red-shifted and bright E₁₁* PL originating from the excitons localized at the defect-doped sites. Here, we observe the E₁₁* PL energy shifts induced by protein adsorption via the avidin-biotin interactions at the doped sites of lf-SWCNTs. We establish that the difference in the structures of the avidin derivatives notably influences the energy shifts. First, lf-SWCNT-tethering biotin groups (lf-SWCNTs-b) are synthesized based on diazonium chemistry, followed by post-modification. The responsiveness of the lf-SWCNTs-b to different microenvironments is investigated, and a correlation between the E₁₁* PL energy shift and the induction-polarity parameters of surrounding solvents is established. The adsorption of neutravidin onto the lf-SWCNTs-b induces an increase in the induction-polarity parameters around the biotin-doped sites, resulting in the red-shift of the E₁₁* PL peak. The E₁₁* PL shift behaviors of the lf-SWCNTs-b change noticeably when avidin and streptavidin are introduced compared to the case with neutravidin. This is due to the different microenvironments formed at the biotin-doped sites, attributed to the difference in the structural features of the introduced avidin derivatives. Moreover, we successfully enhance the detection signals of lf-SWCNTs-b (>three fold) for streptavidin detection using a fabricated film device. Therefore, lf-SWCNTs exhibit significant promise for application in advanced protein detection/recognition devices based on NIR PL.

Wearable Device-Based Smart Football Athlete Health Prediction Algorithm Based on Recurrent Neural Networks

For football players who participate in sports, the word “health” is extremely important. Athletes cannot create their own value in competitive competitions without a strong foundation. Scholars have paid a lot of attention to athlete health this year, and many analysis methods have been proposed, but there have been few studies using neural networks. As a result, this article proposes a novel wearable device-based smart football player health prediction algorithm based on recurrent neural networks. To begin, this article employs wearable sensors to collect health data from football players. The time step data are then fed into a recurrent neural network to extract deep features, followed by the health prediction results. The collected football player health dataset is used in this paper to conduct experiments. The simulation results prove the reliability and superiority of the proposed algorithm. Furthermore, the algorithm presented in this paper can serve as a foundation for the football team's and coaches' scientific training plans.

Validity of a Novel Research-Grade Physical Activity and Sleep Monitor for Continuous Remote Patient Monitoring

In the midst of the COVID-19 pandemic, Remote Patient Monitoring technologies are highly important for clinicians and researchers. These connected-health technologies enable monitoring of patients and facilitate remote clinical trial research while reducing the potential for the spread of the novel coronavirus. There is a growing requirement for monitoring of the full 24 h spectrum of behaviours with a single research-grade sensor. This research describes a free-living and supervised protocol comparison study of the Verisense inertial measurement unit to assess physical activity and sleep parameters and compares it with the Actiwatch 2 actigraph. Fifteen adults (11 males, 23.4 ± 3.4 years and 4 females, 29 ± 12.6 years) wore both monitors for 2 consecutive days and nights in the free-living study while twelve adults (11 males, 23.4 ± 3.4 years and 1 female, 22 ± 0 years) wore both monitors for the duration of a gym-based supervised protocol study. Agreement of physical activity epoch-by-epoch data with activity classification of sedentary, light and moderate-to-vigorous activity and sleep metrics were evaluated using Spearman's rank-order correlation coefficients and Bland-Altman plots. For all activity, Verisense showed high agreement for both free-living and supervised protocol of r = 0.85 and r = 0.78, respectively. For physical activity classification, Verisense showed high agreement of sedentary activity of r = 0.72 for free-living but low agreement of r = 0.36 for supervised protocol; low agreement of light activity of r = 0.42 for free-living and negligible agreement of r = -0.04 for supervised protocol; and moderate agreement of moderate-to-vigorous activity of r = 0.52 for free-living with low agreement of r = 0.49 for supervised protocol. For sleep metrics, Verisense showed moderate agreement for sleep time and total sleep time of r = 0.66 and 0.54, respectively, but demonstrated high agreement for determination of wake time of r = 0.83. Overall, our results showed moderate-high agreement of Verisense with Actiwatch 2 for assessing epoch-by-epoch physical activity and sleep, but a lack of agreement for activity classifications. Future validation work of Verisense for activity cut-point potentially holds promise for 24 h continuous remote patient monitoring.

Evaluation of Remote Monitoring Device for Monitoring Vital Parameters against Reference Standard: A Diagnostic Validation Study for COVID-19 Preparedness

CONTEXT

Vital parameters including blood oxygen level, respiratory rate, pulse rate, and body temperature are crucial for triaging patients to appropriate medical care. Advances in remote health monitoring system and wearable health devices have created a new horizon for delivery of efficient health care from a distance.

MATERIALS AND METHODS

This diagnostic validation study included patients attending the outpatient department of the institute. The accuracy of device under study was compared against the gold standard patient monitoring systems used in intensive care units.

STATISTICAL ANALYSIS

The statistical analysis involved computation of intraclass correlation coefficient. Bland-Altman graphs with limits of agreement were plotted to assess agreement between methods. P <0.05 was considered statistically significant.

RESULTS

A total of 200 patients, including 152 males and 48 females in the age range of 2-80 years, formed the study group. A strong correlation (intraclass correlation coefficient; r > 0.9) was noted between the two devices for all the investigated parameters with significant P value (<0.01). Bland-Altman plot drawn for each vital parameter revealed observations in agreement from both the devices.

CONCLUSION

The wearable device can be reliably used for remote health monitoring. Its regulated use can help mitigate the scarcity of hospital beds and reduce exposure to health-care workers and demand of personal protection equipment.

3D-Printed Sugar Scaffold for High-Precision and Highly Sensitive Active and Passive Wearable Sensors

In this study, a pairing of a previously unidentified 3D printing technique and soft materials is introduced in order to achieve not only high-resolution printed features and flexibility of the 3D-printed materials, but also its light-weight and electrical conductivity. Using the developed technique and materials, high-precision and highly sensitive patient-specific wearable active or passive devices are fabricated for personalized health monitoring. The fabricated biosensors show low density and substantial flexibility because of 3D microcellular network-type interconnected conductive materials that are readily printed using an inkjet head. Using high-resolution 3D scanned body-shape data, on-demand personalized wearable sensors made of the 3D-printed soft and conductive materials are fabricated. These sensors successfully detect both actively changing body strain signals and passively changing signals such as electromyography (EMG), electrodermal activity (EDA), and electroencephalogram EEG. The accurately tailored subject-specific shape of the developed sensors exhibits higher sensitivity and faster real-time sensing performances in the monitoring of rapidly changing human body signals. The newly developed 3D printing technique and materials can be widely applied to various types of wearable, flexible, and light-weight biosensors for use in a variety of inexpensive on-demand and personalized point-of-care diagnostics.

Wrist-worn alcohol biosensors: Strengths, limitations, and future directions

Wearable alcohol biosensors have emerged as a valuable tool for noninvasive, objective, and continuous monitoring of alcohol consumption. However, to date their research and clinical applications have been limited by several factors including large size, high cost, and social stigma. In contrast, recently developed wrist-worn alcohol biosensors are smaller, less expensive, and may be more acceptable for daily use. However, these devices are at the prototype phase and have just begun to be tested for research applications. In this paper, we describe our experiences with two prototypes of these new wrist-worn alcohol biosensors (i.e., Quantac Tally and BACtrack Skyn) and their associated smartphone applications in both a controlled laboratory setting and the real-world environment. Our preliminary experiences with these devices highlight their advantages including comfort, high participant acceptability, and good compliance. However, there are various limitations that should be addressed prior to future research applications of these biosensors, including large interpersonal variations in transdermal alcohol readings, lack of immediately applicable data analysis/interpretation software, and poor battery life after a few months. More research is also needed to further validate the new biosensors, and investigate individual (e.g., skin thickness, gender differences) and environmental factors (e.g., humidity, temperature) contributing to the variations in transdermal alcohol readings measured by wrist-worn alcohol biosensors.

Multi-Sensor Fusion for Activity Recognition-A Survey

In Ambient Intelligence (AmI), the activity a user is engaged in is an essential part of the context, so its recognition is of paramount importance for applications in areas like sports, medicine, personal safety, and so forth. The concurrent use of multiple sensors for recognition of human activities in AmI is a good practice because the information missed by one sensor can sometimes be provided by the others and many works have shown an accuracy improvement compared to single sensors. However, there are many different ways of integrating the information of each sensor and almost every author reporting sensor fusion for activity recognition uses a different variant or combination of fusion methods, so the need for clear guidelines and generalizations in sensor data integration seems evident. In this survey we review, following a classification, the many fusion methods for information acquired from sensors that have been proposed in the literature for activity recognition; we examine their relative merits, either as they are reported and sometimes even replicated and a comparison of these methods is made, as well as an assessment of the trends in the area.

Intraindividual Variability Measurement of Fine Manual Motor Skills in Children Using an Electronic Pegboard: Cohort Study

Background

Pegboard tests are a powerful technique used by health and education professionals to evaluate manual dexterity and fine motor speed, both in children and adults. Using traditional pegboards in tests, the total time that, for example, a 4-year-old child needs for inserting pegs in a pegboard, with the left or right hand, can be measured. However, these measurements only allow for studying the variability among individuals, whereas no data can be obtained on the intraindividual variability in inserting and removing these pegs with one and the other hand.

Objective

The aim of this research was to study the intraindividual variabilities in fine manual motor skills of 2- to 3-year-old children during playing activities, using a custom designed electronic pegboard.

Methods

We have carried out a pilot study with 39 children, aged between 25 and 41 months. The children were observed while performing a task involving removing 10 pegs from 10 holes on one side and inserting them in 10 holes on the other side of a custom-designed sensor-based electronic pegboard, which has been built to be able to measure the times between peg insertions and removals.

Results

A sensor-based electronic pegboard was successfully developed, enabling the collection of single movement time data. In the piloting, a lower intraindividual variability was found in children with lower placement and removal times, confirming Adolph et al’s hypothesis.

Conclusions

The developed pegboard allows for studying intraindividual variability using automated wirelessly transmitted data provided by its sensors. This novel technique has been useful in studying and validating the hypothesis that children with lower movement times present lower intraindividual variability. New research is necessary to confirm these findings. Research with larger sample sizes and age ranges that include additional testing of children’s motor development level is currently in preparation.

Synthetic molecular recognition nanosensor paint for microalbuminuria

Microalbuminuria is an important clinical marker of several cardiovascular, metabolic, and other diseases such as diabetes, hypertension, atherosclerosis, and cancer. The accurate detection of microalbuminuria relies on albumin quantification in the urine, usually via an immunoturbidity assay; however, like many antibody-based assessments, this method may not be robust enough to function in global health applications, point-of-care assays, or wearable devices. Here, we develop an antibody-free approach using synthetic molecular recognition by constructing a polymer to mimic fatty acid binding to the albumin, informed by the albumin crystal structure. A single-walled carbon nanotube, encapsulated by the polymer, as the transduction element produces a hypsochromic (blue) shift in photoluminescence upon the binding of albumin in clinical urine samples. This complex, incorporated into an acrylic material, results in a nanosensor paint that enables the detection of microalbuminuria in patient samples and comprises a rapid point-of-care sensor robust enough to be deployed in resource-limited settings.

Subjective feelings of appetite of wholegrain breakfasts evaluated under controlled, laboratory and 'at home' conditions

BACKGROUND

Appetite regulating properties of foods are usually investigated under laboratory conditions, whereas in real life, foods are consumed under at home conditions. The objective of this study was to compare the acute effects of breakfasts when tested in a laboratory condition and in an at home condition. Appetite regulating properties of two bread breakfasts and two cereal breakfasts were also compared.

SUBJECTS AND METHODS

In this randomized cross-over trial balanced for laboratory and at home test conditions, thirty-two women consumed five breakfasts, i.e. two bread breakfasts, two cereal breakfasts and one fried-egg breakfast. Visual analogue scales for measuring appetite were captured via an on-line scoring system and were analyzed as incremental area under the curve, as satiation phase and as satiety phase.

RESULTS

Location effects were limited to two small effects only. An overall location effect in hunger feelings was observed (p = 0.040), which occurred specifically during the short satiation period (p = 0.0002) where hunger feelings scored higher under laboratory conditions. Similarly, a location effect was observed for desire to eat (p = 0.001); this was again higher under laboratory conditions. No other location effects were observed. Bread breakfasts did not differ in their appetite regulating properties. The Steel Cut oatmeal breakfast was reported to be more satiating (p = 0.001) as compared to the ready-to-eat cereal.

CONCLUSIONS

Whereas the five breakfasts varied somewhat in their appetite regulating properties, evaluation under laboratory conditions overall did not result in different appetite scores compared to the at home conditions. This suggests that at home testing may be a useful alternative to laboratory test conditions for nutrition research.

Longitudinal Walking Analysis in Hemiparetic Patients Using Wearable Motion Sensors: Is There Convergence Between Body Sides?

Background: Longitudinal movement parameter analysis of hemiparetic patients over several months could reveal potential recovery trends and help clinicians adapting therapy strategies to maximize recovery outcome. Wearable sensors offer potential for day-long movement recordings in realistic rehabilitation settings including activities of daily living, e.g., walking. The measurement of walking-related movement parameters of affected and non-affected body sides are of interest to determine mobility and investigate recovery trends. Methods: By comparing movement of both body sides, recovery trends across the rehabilitation duration were investigated. We derived and validated selected walking segments from free-living, day-long movement by using rules that do not require data-based training or data annotations. Automatic stride segmentation using peak detection was applied to walking segments. Movement parameters during walking were extracted, including stride count, stride duration, cadence, and sway. Finally, linear regression models over each movement parameter were derived to forecast the moment of convergence between body sides. Convergence points were expressed as duration and investigated in a patient observation study. Results: Convergence was analyzed in walking-related movement parameters in an outpatient study including totally 102 full-day recordings of inertial movement data from 11 hemiparetic patients. The recordings were performed over several months in a day-care centre. Validation of the walking extraction method from sensor data yielded sensitivities up to 80 % and specificity above 94 % on average. Comparison of automatically and manually derived movement parameters showed average relative errors below 6 % between affected and non-affected body sides. Movement parameter variability within and across patients was observed and confirmed by case reports, reflecting individual patient behavior. Conclusion: Convergence points were proposed as intuitive metric, which could facilitate training personalization for patients according to their individual needs. Our continuous movement parameter extraction and analysis, was feasible for realistic, day-long recordings without annotations. Visualizations of movement parameter trends and convergence points indicated that individual habits and patient therapies were reflected in walking and mobility. Context information of clinical case reports supported trend and convergence interpretation. Inconsistent convergence point estimation suggested individually varying deficiencies. Long-term recovery monitoring using convergence points could support patient-specific training strategies in future remote rehabilitation.

Connected Health Devices for Health Care in French General Medicine Practice: Cross-Sectional Study

Background

The integration of Connected Health Devices (CHDs) is growing within mobile health (mHealth) and telemedicine, encouraged by institutions and industries. The idea is to improve lifestyle habits and health behaviors as a preventive goal in an aging population with fewer physicians available. However, their ill-defined place in health care does not promote their use in current medical practice.

Objective

The primary objective of this study was to quantify CHDs’ use rate by general practitioners (GPs). A secondary objective was to evaluate their benefits and limitations in usual care.

Methods

A cross-sectional study through an Internet-based survey was addressed to French GPs via regional medical unions and continuous education agencies, supplemented with an informative website, from March 2015 to July 2015. Surveys where either the form was insufficiently filled or the main question was left unanswered were excluded from the study.

Results

A total of 1084 answers were analyzed, of which 19.46% (211/1084, 95% CI 17.1-21.8) GPs used CHDs, and 10.15% (110/1084, 95% CI 8.5-12.1) prescribed a CHD. CHD users statistically prescribed more CHDs (7.38% [80/1084] in the user group vs 2.86% [31/1084] in nonusers; P<.001) and were more likely to use them in the future. Major interests in their utilization were in patient monitoring for 84.96% (921/1084) and patient education for 75.83% (822/1084), especially for diabetes (89.67%, 972/1084) and hypertension (84.13%, 912/1084). Generated data had to be managed securely by the patient primarily for 85.79% (930/1084) of the GPs. CHDs had to not constrain GPs outside clinical consultation, nor restrain their time for 75.83% (822/1084). Additional actors in patient care were not desired for 79.98% (867/1084) of the GPs. Questions about data management issues and technical difficulties were raised.

Conclusions

CHDs are little used by French GPs and even less prescribed to their patients, as only a few GPs use these tools. Their benefits as tools of patient empowerment, although expected, remain to be demonstrated in real-life setups.

The role of tele-medicine in patients with respiratory diseases

INTRODUCTION

Tele-medicine is a clinical application connecting a patient with specialized care consultants by means of electronic platforms, potentially able to improve patients' self-management and allow for the care of patients with limited access to health services. This article summarizes the use of tele-medicine as a tool in managing patients suffering from some pathological respiratory conditions. Areas covered: We searched papers published between 1990 and 2017 dealing with tele-medicine and respiratory diseases, chronic obstructive pulmonary disease, asthma, interstitial lung disease, chronic respiratory failure, neuromuscular diseases, critical illness, home mechanical ventilation, and also legal and economic issues. Controlled trials report different results on feasibility, cost-effectiveness, and safety of tele-medicine. Expert commentary: Progress in tele-medicine widens the horizons in respiratory medicine: this tool may potentially reduce health care costs by moving some medical interventions from centralized locations in to patient's home, also allowing for the delivery of care in countries with limited access to it. Legal, safety, and privacy problems, as well as reimbursement issues, must still be defined and solved. At present time, we still need much more evidence to consider this modality as a real option in the management of these patients.

Effects of Flexible Dry Electrode Design on Electrodermal Activity Stimulus Response Detection

OBJECTIVE

The focus of this research is to evaluate the effects of design parameters including surface area, distance between and geometry of dry flexible electrodes on electrodermal activity (EDA) stimulus response detection.

METHODS

EDA is a result of the autonomic nervous system being stimulated, which causes sweat and changes the electrical characteristics of the skin. Standard silver/silver chloride (Ag/AgCl) EDA electrodes are rigid and lack conformability in contact with skin. In this study, flexible dry Ag/AgCl EDA electrodes were fabricated on a compliant substrate, used to monitor EDA stimulus responses and compared to results simultaneously collected by rigid dry Ag/AgCl electrodes.

RESULTS

A repeatable fabrication process for flexible Ag/AgCl electrodes has been established. Surface area, distance between and geometry of electrodes are shown to affect the detectability of the EDA response and the minimum number of sweat glands to be covered by the electrodes has been estimated at 140, or more, in order to maintain functionality. The optimal flexible EDA electrode is a serpentine design with a 0.15 cm² surface area and a 0.20 cm distance with an average Pearson correlation coefficient of .

CONCLUSION

Fabrication of flexible electrodes is described and an understanding of the effects of electrode designs on the EDA stimulus response detection has been established and is potentially related to the coverage of sweat glands.

SIGNIFICANCE

This work presents a novel systematic approach to understand the effects of electrode designs on monitoring EDA which is of importance for the design of wearable EDA monitoring devices.

Wearable technology: role in respiratory health and disease

In the future, diagnostic devices will be able to monitor a patient’s physiological or biochemical parameters continuously, under natural physiological conditions and in any environment through wearable biomedical sensors. Together with apps that capture and interpret data, and integrated enterprise and cloud data repositories, the networks of wearable devices and body area networks will constitute the healthcare’s Internet of Things. In this review, four main areas of interest for respiratory healthcare are described: pulse oximetry, pulmonary ventilation, activity tracking and air quality assessment. Although several issues still need to be solved, smart wearable technologies will provide unique opportunities for the future or personalised respiratory medicine.

Smart wearable technologies provide unique opportunities for assessing and monitoring respiratory functionhttp://ow.ly/BHXY30cEfBl

A ROBUST AUTOMATIC GAIT MONITORING APPROACH USING A SINGLE IMU FOR HOME-BASED APPLICATIONS

A new approach of human activity monitoring with a single Inertial Measurement Unit (IMU) capable of gait recognition and assessment is proposed for home-based applications. The method estimates the foot motion using a single IMU, then automatically segments the motion into steps, and extracts multiple kinematics templates. It classifies each segment by extracting Mahalanobis distance-based features from multiple sections of the motion templates and then training a Support Vector Machine. The proposed wearable system can distinguish between nine classes of activities with a classification accuracy of 99.6%. It can also discriminate between normal and abnormal gait patterns with an accuracy of 98.7%. In addition to a high recognition rate, the proposed approach provides a Gait Similarity Score (GSS) of the performed gait to its desired/normal pattern. The experimental results indicate the capability of GSS measure for assessing the quality of motion in “pre-”, “initial”, “mid” and “terminal” stages of swing phase.

A Smart Toy to Enhance the Decision-Making Process at Children's Psychomotor Delay Screenings: A Pilot Study

BACKGROUND

EDUCERE ("Ubiquitous Detection Ecosystem to Care and Early Stimulation for Children with Developmental Disorders") is an ecosystem for ubiquitous detection, care, and early stimulation of children with developmental disorders. The objectives of this Spanish government-funded research and development project are to investigate, develop, and evaluate innovative solutions to detect changes in psychomotor development through the natural interaction of children with toys and everyday objects, and perform stimulation and early attention activities in real environments such as home and school. Thirty multidisciplinary professionals and three nursery schools worked in the EDUCERE project between 2014 and 2017 and they obtained satisfactory results. Related to EDUCERE, we found studies based on providing networks of connected smart objects and the interaction between toys and social networks.

OBJECTIVE

This research includes the design, implementation, and validation of an EDUCERE smart toy aimed to automatically detect delays in psychomotor development. The results from initial tests led to enhancing the effectiveness of the original design and deployment. The smart toy, based on stackable cubes, has a data collector module and a smart system for detection of developmental delays, called the EDUCERE developmental delay screening system (DDSS).

METHODS

The pilot study involved 65 toddlers aged between 23 and 37 months (mean=29.02, SD 3.81) who built a tower with five stackable cubes, designed by following the EDUCERE smart toy model. As toddlers made the tower, sensors in the cubes sent data to a collector module through a wireless connection. All trials were video-recorded for further analysis by child development experts. After watching the videos, experts scored the performance of the trials to compare and fine-tune the interpretation of the data automatically gathered by the toy-embedded sensors.

RESULTS

Judges were highly reliable in an interrater agreement analysis (intraclass correlation 0.961, 95% CI 0.937-0.967), suggesting that the process was successful to separate different levels of performance. A factor analysis of collected data showed that three factors, trembling, speed, and accuracy, accounted for 76.79% of the total variance, but only two of them were predictors of performance in a regression analysis: accuracy (P=.001) and speed (P=.002). The other factor, trembling (P=.79), did not have a significant effect on this dependent variable.

CONCLUSIONS

The EDUCERE DDSS is ready to use the regression equation obtained for the dependent variable "performance" as an algorithm for the automatic detection of psychomotor developmental delays. The results of the factor analysis are valuable to simplify the design of the smart toy by taking into account only the significant variables in the collector module. The fine-tuning of the toy process module will be carried out by following the specifications resulting from the analysis of the data to improve the efficiency and effectiveness of the product.

Metabolomics for the masses: The future of metabolomics in a personalized world

Current clinical practices focus on a small number of biochemical directly related to the pathophysiology with patients and thus only describe a very limited metabolome of a patient and fail to consider the interations of these small molecules. This lack of extended information may prevent clinicians from making the best possible therapeutic interventions in sufficient time to improve patient care. Various post-genomics '('omic)' approaches have been used for therapeutic interventions previously. Metabolomics now a well-established'omics approach, has been widely adopted as a novel approach for biomarker discovery and in tandem with genomics (especially SNPs and GWAS) has the potential for providing systemic understanding of the underlying causes of pathology. In this review, we discuss the relevance of metabolomics approaches in clinical sciences and its potential for biomarker discovery which may help guide clinical interventions. Although a powerful and potentially high throughput approach for biomarker discovery at the molecular level, true translation of metabolomics into clinics is an extremely slow process. Quicker adaptation of biomarkers discovered using metabolomics can be possible with novel portable and wearable technologies aided by clever data mining, as well as deep learning and artificial intelligence; we shall also discuss this with an eye to the future of precision medicine where metabolomics can be delivered to the masses.

Smart Toys Designed for Detecting Developmental Delays

In this paper, we describe the design considerations and implementation of a smart toy system, a technology for supporting the automatic recording and analysis for detecting developmental delays recognition when children play using the smart toy. To achieve this goal, we take advantage of the current commercial sensor features (reliability, low consumption, easy integration, etc.) to develop a series of sensor-based low-cost devices. Specifically, our prototype system consists of a tower of cubes augmented with wireless sensing capabilities and a mobile computing platform that collect the information sent from the cubes allowing the later analysis by childhood development professionals in order to verify a normal behaviour or to detect a potential disorder. This paper presents the requirements of the toy and discusses our choices in toy design, technology used, selected sensors, process to gather data from the sensors and generate information that will help in the decision-making and communication of the information to the collector system. In addition, we also describe the play activities the system supports.

Analyzing older users' home telehealth services acceptance behavior-applying an Extended UTAUT model

BACKGROUND

Although telehealth offers an improved approach to providing healthcare services, its adoption by end users remains slow. With an older population as the main target, these traditionally conservative users pose a big challenge to the successful implementation of innovative telehealth services.

OBJECTIVES

The objective of this study was to develop and empirically test a model for predicting the factors affecting older users' acceptance of Home Telehealth Services (HTS).

METHODS

A survey instrument was administered to 400 participants aged 50 years and above from both rural and urban environments in Slovenia. Structural equation modeling was applied to analyze the causal effect of seven hypothesized predicting factors. HTS were introduced as a bundle of functionalities, representing future services that currently do not exist. This enabled users' perceptions to be measured on the conceptual level, rather than attitudes to a specific technical solution.

RESULTS

Six relevant predictors were confirmed in older users' HTS acceptance behavior, with Performance Expectancy (r=0.30), Effort Expectancy (r=0.49), Facilitating Conditions (r=0.12), and Perceived Security (r=0.16) having a direct impact on behavioral intention to use HTS. In addition, Computer Anxiety is positioned as an antecedent of Effort Expectancy with a strong negative influence (r=-0.61), and Doctor's Opinion influence showed a strong impact on Performance Expectancy (r=0.31). The results also indicate Social Influence as an irrelevant predictor of acceptance behavior. The model of six predictors yielded 77% of the total variance explained in the final measured Behavioral Intention to Use HTS by older adults.

CONCLUSION

The level at which HTS are perceived as easy to use and manage is the leading acceptance predictor in older users' HTS acceptance. Together with Perceived Usefulness and Perceived Security, these three factors represent the key influence on older people's HTS acceptance behavior. When promoting HTS, interventions should focus to portray it as secure. Marketing interventions should focus also on promoting HTS among health professionals, using them as social agents to frame the services as useful and beneficial. The important role of computer anxiety may result in a need to use different equipment such as a tablet computer to access HTS. Finally, this paper introduces important methodological guidelines for measuring perceptions on a conceptual level of future services that currently do not exist.

Recent Directions in Telemedicine: Review of Trends in Research and Practice

Objectives

Healthcare is now routinely delivered by telecommunications-based services in all developed countries and an increasing number of developing countries. Telemedicine is used in many clinical specialities and across numerous healthcare settings, which range from mobile patient-centric applications to complex interactions amongst clinicians in tertiary referral hospital settings. This paper discusses some recent areas of significant development and progress in the field with the purpose of identifying strong trends in both research and practice activities.

Methods

To establish the breadth of new ideas and directions in the field, a review of literature was made by searching PubMed for recent publications including terms (telemedicine OR telehealth) AND (challenge OR direction OR innovation OR new OR novel OR trend), for all searchable categories. 3,433 publications were identified that have appeared since January 1, 2005 (2,172 of these since January 1, 2010), based on a search conducted on June 1, 2015.

Results

The current interest areas in these papers span both synchronous telemedicine, including intensive care, emergency medicine, and mental health, and asynchronous telemedicine, including wound and burns care, dermatology and ophthalmology.

Conclusions

It is concluded that two major drivers of contemporary tele medicine development are a high volume demand for a particular clinical service, and/or a high criticality of need for clinical exper tise to deliver the service. These areas offer promise for further study and enhancement of applicable telemedicine methods and have the potential for large-scale deployments internationally, which would contribute significantly to the advancement of healthcare.

Nursing informatics: decades of contribution to health informatics

OBJECTIVES

In this paper we present a contemporary understanding of "nursing informatics" and relate it to applications in three specific contexts, hospitals, community health, and home dwelling, to illustrate achievements that contribute to the overall schema of health informatics.

METHODS

We identified literature through database searches in MEDLINE, EMBASE, CINAHL, and the Cochrane Library. Database searching was complemented by one author search and hand searches in six relevant journals. The literature review helped in conceptual clarification and elaborate on use that are supported by applications in different settings.

RESULTS

Conceptual clarification of nursing data, information and knowledge has been expanded to include wisdom. Information systems and support for nursing practice benefits from conceptual clarification of nursing data, information, knowledge, and wisdom. We introduce three examples of information systems and point out core issues for information integration and practice development.

CONCLUSIONS

Exploring interplays of data, information, knowledge, and wisdom, nursing informatics takes a practice turn, accommodating to processes of application design and deployment for purposeful use by nurses in different settings. Collaborative efforts will be key to further achievements that support task shifting, mobility, and ubiquitous health care.

Sensors: views of staff of a disability service organization

Sensors have become ubiquitous in their reach and scope of application. They are a technological cornerstone for various modes of health surveillance and participatory medicine-such as quantifying oneself; they are also employed to track people with certain as impairments perceived ability differences. This paper presents quantitative and qualitative data of an exploratory, non-generalizable study into the perceptions, attitudes and concerns of staff of a disability service organization, that mostly serve people with intellectual disabilities, towards the use of various types of sensor technologies that might be used by and with their clients. In addition, perspectives of various types of privacy issues linked to sensors, as well data regarding the concept of quantified self were obtained. Our results highlight the need to involve disabled people and their support networks in sensor and quantified-self discourses, in order to prevent undue disadvantages.