The Importance of Real-World Validation of Machine Learning Systems in Wearable Exercise Biofeedback Platforms: A Case Study.

Machine learning models are being utilized to provide wearable sensor-based exercise biofeedback to patients undertaking physical therapy. However, most systems are validated at a technical level using lab-based cross validation approaches. These results do not necessarily reflect the performance levels that patients and clinicians can expect in the real-world environment.

Corona citizens' science project-repeated surveys of the Irish response to COVID-19 and subsequent lockdown and restrictive measures.

Background: Worldwide, many people have been affected by COVID-19, a novel respiratory illness, caused by a new type of coronavirus SARS-CoV2. The COVID-19 outbreak is considered a pandemic and has created a number of challenges for the general population, patients, and healthcare professionals. Lockdowns have been implemented to slow down the spread of the virus with the expectation that these restrictions will limit the number of cases, and hence the number of hospitalizations and ICU admissions.

Three datasets reporting unexpected events for everyday scenarios: Over 9000 events human-labelled for overall valence/sentiment, topic category, and relationship to the initial goal of the scenario.

The three datasets described in this paper were collected from online experiments distributed via Prolific.co participant system. Together, the three datasets comprise 9720 text responses of unexpected events participants predicted for everyday scenarios such as going shopping or preparing breakfast.

Concussion History and Balance Performance in Adolescent Rugby Union Players.

Background: Sports-related concussion is a worldwide problem. There is a concern that an initial concussion can cause prolonged subclinical disturbances to sensorimotor function that increase the risk of subsequent injury. The primary aim of this study was to examine whether a history of sports-related concussion has effects on static and dynamic balance performance in adolescent rugby players.

Use of standardized terminologies in clinical practice: A scoping review.

Aim: To explore the use and impact of standardized terminologies (STs) within nursing and midwifery practice.

Introduction: The standardization of clinical documentation creates a potential to optimize patient care and safety. Nurses and midwives, who represent the largest proportion of the healthcare workforce worldwide, have been using nursing-specific and multidisciplinary STs within electronic health records (EHRs) for decades.

Quantitatively Measuring Privacy in Interactive Query Settings Within RDBMS Framework.

Little attention has been paid to the measurement of risk to privacy in Database Management Systems, despite their prevalence as a modality of data access. This paper proposes , a quantitative privacy metric that provides a measure (privacy score) of privacy risk when executing queries in relational database management systems. PriDe measures the degree to which attribute values, retrieved by a principal (user) engaging in an interactive query session, represent a reduction of privacy with respect to the attribute values previously retrieved by the principal.

Discovering symptom patterns of COVID-19 patients using association rule mining.

Background: The COVID-19 pandemic is a significant public health crisis that is hitting hard on people's health, well-being, and freedom of movement, and affecting the global economy. Scientists worldwide are competing to develop therapeutics and vaccines; currently, three drugs and two vaccine candidates have been given emergency authorization use. However, there are still questions of efficacy with regard to specific subgroups of patients and the vaccine's scalability to the general public.

Internet of Robotic Things Intelligent Connectivity and Platforms.

The Internet of Things (IoT) and Industrial IoT (IIoT) have developed rapidly in the past few years, as both the Internet and "things" have evolved significantly. "Things" now range from simple Radio Frequency Identification (RFID) devices to smart wireless sensors, intelligent wireless sensors and actuators, robotic things, and autonomous vehicles operating in consumer, business, and industrial environments. The emergence of "intelligent things" (static or mobile) in collaborative autonomous fleets requires new architectures, connectivity paradigms, trustworthiness frameworks, and platforms for the integration of applications across different business and industrial domains.

Reliability of inertial sensor based spatiotemporal gait parameters for short walking bouts in community dwelling older adults.

Background: When performing quantitative analysis of gait in older adults we need to strike a balance between capturing sufficient data for reliable measurement and avoiding issues such as fatigue. The optimal bout duration is that which contains sufficient gait cycles to enable a reliable and representative estimate of gait performance.

Research Question: How does the number of gait cycles in a walking bout influence reliability of spatiotemporal gait parameters measured using body-worn inertial sensors in a cohort of community dwelling older adults?

Methods: One hundred and fifteen (115) community dwelling older adults executed three 30-metre walk trials in a single measurement session.

Meal Pattern Analysis in Nutritional Science: Recent Methods and Findings.

There is a scarcity of dietary intake research focusing on the intake of whole meals rather than on the nutrients and foods of which those meals are composed. This growing area of research has recently begun to utilize advanced statistical techniques to manage the large number of variables and permutations associated with these complex meal patterns. The aim of this narrative review was to evaluate those techniques and the meal patterns they detect.

A Roadmap to Inform Development, Validation and Approval of Digital Mobility Outcomes: The Mobilise-D Approach.

Health care has had to adapt rapidly to COVID-19, and this in turn has highlighted a pressing need for tools to facilitate remote visits and monitoring. Digital health technology, including body-worn devices, offers a solution using digital outcomes to measure and monitor disease status and provide outcomes meaningful to both patients and health care professionals. Remote monitoring of physical mobility is a prime example, because mobility is among the most advanced modalities that can be assessed digitally and remotely.

Dynamics of cascades on burstiness-controlled temporal networks.

Burstiness, the tendency of interaction events to be heterogeneously distributed in time, is critical to information diffusion in physical and social systems. However, an analytical framework capturing the effect of burstiness on generic dynamics is lacking. Here we develop a master equation formalism to study cascades on temporal networks with burstiness modelled by renewal processes.

Recommendations for determining the validity of consumer wearable heart rate devices: expert statement and checklist of the INTERLIVE Network.

Assessing vital signs such as heart rate (HR) by wearable devices in a lifestyle-related environment provides widespread opportunities for public health related research and applications. Commonly, consumer wearable devices assessing HR are based on photoplethysmography (PPG), where HR is determined by absorption and reflection of emitted light by the blood. However, methodological differences and shortcomings in the validation process hamper the comparability of the validity of various wearable devices assessing HR.

Recommendations for determining the validity of consumer wearable and smartphone step count: expert statement and checklist of the INTERLIVE network.

Consumer wearable and smartphone devices provide an accessible means to objectively measure physical activity (PA) through step counts. With the increasing proliferation of this technology, consumers, practitioners and researchers are interested in leveraging these devices as a means to track and facilitate PA behavioural change. However, while the acceptance of these devices is increasing, the validity of many consumer devices have not been rigorously and transparently evaluated.

Physiotherapists' Use of Web-Based Information Resources to Fulfill Their Information Needs During a Theoretical Examination: Randomized Crossover Trial.

Background: The widespread availability of internet-connected smart devices in the health care setting has the potential to improve the delivery of research evidence to the care pathway and fulfill health care professionals' information needs.

Objective: This study aims to evaluate the frequency with which physiotherapists experience information needs, the capacity of digital information resources to fulfill these needs, and the specific types of resources they use to do so.

Methods: A total of 38 participants (all practicing physiotherapists; 19 females, 19 males) were randomly assigned to complete three 20-question multiple-choice questionnaire (MCQ) examinations under 3 conditions in a randomized crossover study design: assisted by a web browser, assisted by a federated search portal system, and unassisted.

Do we "fear for the worst" or "Hope for the best" in thinking about the unexpected?: Factors affecting the valence of unexpected outcomes reported for everyday scenarios.

Though we often "fear the worst", worrying that unexpectedly bad things will happen, there are times when we "hope for the best", imagining that unexpectedly good things will happen, too. The paper explores how the valence of the current situation influences people's imagining of unexpected future events when participants were instructed to think of "something unexpected". In Experiment 1, participants (N = 127) were asked to report unexpected events to everyday scenarios under different instructional conditions (e.

Radiology artificial intelligence, a systematic evaluation of methods (RAISE): a systematic review protocol.

Introduction: There has been a recent explosion of research into the field of artificial intelligence as applied to clinical radiology with the advent of highly accurate computer vision technology. These studies, however, vary significantly in design and quality. While recent guidelines have been established to advise on ethics, data management and the potential directions of future research, systematic reviews of the entire field are lacking.

Using functional movement tests to investigate the presence of sensorimotor impairment in amateur athletes following sport-related concussion: A prospective, longitudinal study.

Objective: To longitudinally investigate the presence of sensorimotor impairments in amateur athletes following sport-related concussion using two functional movement tests.

Design: Prospective, longitudinal study.

Setting: Human movement analysis laboratory.

Establishing consensus on key public health indicators for the monitoring and evaluating childhood obesity interventions: a Delphi panel study.

Background: Childhood obesity is influenced by myriad individual, societal and environmental factors that are not typically reflected in current interventions. Socio-ecological conditions evolve and require ongoing monitoring in terms of assessing their influence on child health. The aim of this study was to identify and prioritise indicators deemed relevant by public health authorities for monitoring and evaluating childhood obesity interventions.

Prevalence and frequency of menstrual cycle symptoms are associated with availability to train and compete: a study of 6812 exercising women recruited using the Strava exercise app.

Objectives: The menstrual cycle can affect sports participation and exercise performance. There are very few data on specific menstrual cycle symptoms (symptoms during various phases of the cycle, not only during menstruation) experienced by exercising women. We aimed to characterise the most common symptoms, as well as the number and frequency of symptoms, and evaluate whether menstrual cycle symptoms are associated with sporting outcomes.

A Thorough Examination of Morning Activity Patterns in Adults with Arthritis and Healthy Controls Using Actigraphy Data.

Background: Wearable sensors allow researchers to remotely capture digital health data, including physical activity, which may identify digital biomarkers to differentiate healthy and clinical cohorts. To date, research has focused on high-level data (e.g.

Exploring the relationships between fundamental movement skills and health related fitness components in children.

This study examined the relationship between fundamental movement skills (FMS) and health related fitness (HRF) components in children. A cross section of Irish primary school children across all age groups participated in this study (n=2098, 47% girls, age 5-12 years of age, mean age 9.2 ± 2.

A comprehensive review of catchment water quality monitoring using a tiered framework of integrated sensing technologies.

Due to the growing threat of climate change, new advances in water quality monitoring strategies are needed now more than ever. Reliable and robust monitoring practices can be used to improve and better understand catchment processes affecting the water quality. In recent years the deployment of long term in-situ sensors has increased the temporal and spatial data being obtained.

Toward a Regulatory Qualification of Real-World Mobility Performance Biomarkers in Parkinson's Patients Using Digital Mobility Outcomes.

Wearable inertial sensors can be used to monitor mobility in real-world settings over extended periods. Although these technologies are widely used in human movement research, they have not yet been qualified by drug regulatory agencies for their use in regulatory drug trials. This is because the first generation of these sensors was unreliable when used on slow-walking subjects.