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Parkinson’s disease is a degenerative neurological disorder that impairs motor functions and is accompanied by a wide range of non-motor symptoms, such as sleep problems. Parkinsonism is assessed during clinical evaluations and via self-administered diaries and, based on these, the required medication therapies are provided to lessen symptoms. Tri-axial accelerometers and gyroscopes have the potential utility to objectively assess the patient’s condition and aid clinicians in their decision-making. People with Parkinson’s often have significant abnormalities in blood pressure due to comorbid age-related cardiovascular disease and orthostatic hypotension, which result in blurred vision, dizziness, and falls. Frequent blood pressure monitoring may aid in the evaluation of such events and differentiate Parkinson’s disease symptoms from those originated by hypotension. In the present paper, a novel technology for the remote monitoring of Parkinsonian symptoms is presented: the WESAA system. It consists of two devices, worn on the wrist and ankle; its main function is to record accelerations and angular velocities from these body parts, together with photoplethysmograph and electrocardiogram data. This information can be elaborated offline to measure common Parkinson’s disease motor symptoms (e.g., tremor, bradykinesia, and dyskinesia), as well as gait speed, sleep-wake cycles, and cuff-less blood pressure measurements. The overall system requirements, market overview, industrial design and ergonomics, system development, user experience, early results of the gathered inertial raw data, and validation of the photoplethysmograph and electrocardiogram signal waveforms are all thoroughly discussed. The developed technology satisfies all system requirements, and the sensors adopted provided outcomes comparable with gold standard techniques.

BackgroundThe increased use of wearable sensor technology has highlighted the potential for remote telehealth services such as rehabilitation. Telehealth services incorporating wearable sensors are most likely to appeal to the older adult population in remote and rural areas, who may struggle with long commutes to clinics. However, the usability of such systems often discourages patients from adopting these services. ObjectiveThis study aimed to understand the usability factors that most influence whether an older adult will decide to continue using a wearable device. MethodsOlder adults across 4 different regions (Northern Ireland, Ireland, Sweden, and Finland) wore an activity tracker for 7 days under a free-living environment protocol. In total, 4 surveys were administered, and biometrics were measured by the researchers before the trial began. At the end of the trial period, the researchers administered 2 further surveys to gain insights into the perceived usability of the wearable device. These were the standardized System Usability Scale (SUS) and a custom usability questionnaire designed by the research team. Statistical analyses were performed to identify the key factors that affect participants’ intention to continue using the wearable device in the future. Machine learning classifiers were used to provide an early prediction of the intention to continue using the wearable device. ResultsThe study was conducted with older adult volunteers (N=65; mean age 70.52, SD 5.65 years) wearing a Xiaomi Mi Band 3 activity tracker for 7 days in a free-living environment. The results from the SUS survey showed no notable difference in perceived system usability regardless of region, sex, or age, eliminating the notion that usability perception differs based on geographical location, sex, or deviation in participants’ age. There was also no statistically significant difference in SUS score between participants who had previously owned a wearable device and those who wore 1 or 2 devices during the trial. The bespoke usability questionnaire determined that the 2 most important factors that influenced an intention to continue device use in an older adult cohort were device comfort (τ=0.34) and whether the device was fit for purpose (τ=0.34). A computational model providing an early identifier of intention to continue device use was developed using these 2 features. Random forest classifiers were shown to provide the highest predictive performance (80% accuracy). After including the top 8 ranked questions from the bespoke questionnaire as features of our model, the accuracy increased to 88%. ConclusionsThis study concludes that comfort and accuracy are the 2 main influencing factors in sustaining wearable device use. This study suggests that the reported factors influencing usability are transferable to other wearable sensor systems. Future work will aim to test this hypothesis using the same methodology on a cohort using other wearable technologies.

Climate change is associated with an increased frequency and intensity of heat waves, posing a threat of heat stress to pig production. Heat stress compromises the efficiency of pig production partly due to causing oxidative stress, intestinal dysfunction, and inflammatory responses. Superoxide dismutase is an antioxidant enzyme reported to reduce oxidative stress and inflammation. Therefore, this experiment aimed to investigate whether recombinant superoxide dismutase (rSOD) could ameliorate oxidative stress and inflammatory responses in heat-stressed grower pigs. Sixty-four female pigs (Large White × Landrace, 27.8 ± 1.65 kg, mean ± SD) were randomly allocated to a control diet (standard grower feed, CON) or the control diet supplemented with 50 IU recombinant superoxide dismutase (rSOD) for 14 days. After acclimation to the diet, pigs were then housed under thermoneutral (TN, 20 °C, 35–50% relative humidity) or cyclic heat stress conditions (CHS, at 35 °C: 9 a.m. to 5 p.m. and 28 °C: 5 p.m. to 9 a.m., 35–50% relative humidity) for 3 days. Heat stress increased respiration rate (RR), skin and rectal temperature (RR and RT) (p < 0.001 for all), and reduced plasma thyroid hormone concentration (p < 0.001). The amount of oxidized glutathione (GSH:GSSG) was increased in the jejunum and ileum of CHS pigs. In the jejunum, rSOD also increased the amount of oxidized glutathione in both TN and CHS pigs, without any change in endogenous SOD activity. In the ileum, rSOD prevented increases in oxidized glutathione formation in the CHS pigs only. Taken together, this may reflect increased oxidative stress in both the jejunum and ileum in CHS pigs. Alternatively, rSOD increased the conversion of reduced to oxidized glutathione independently of CHS, possibly reflecting an increased overall SOD activity due to the addition of exogenous SOD. In conclusion, the use of in-feed SOD enzymes at a dose of 50 IU/kg may be a useful strategy for preventing oxidative stress in pigs.

The purpose of this paper is to develop a better understanding of how to define a positive climate for inclusiveness that recognizes the context and social environment of participants. In order to study employees working with Indigenous people and minorities in four organizations, we used a grounded research approach to define what an inclusive environment might look like. The interview questions gathered examples of experiences which employees valued because they felt more included and not excluded from people they worked with. The experiences fell into four categories, as follows: (i) leadership engaged in supporting inclusiveness within the organization; (ii) leadership engaged in seeking inclusiveness within the community; (iii) being involved in multicultural practices within the organization and community; and (iv) participating in initiatives which encourage engagement and involvement. This paper’s conceptualization of a climate of inclusion is different from other studies, possibly because of the unique context in which service organizations are placed, as such organizations typically work with Indigenous people and minorities. Although we are especially mindful of the danger of generalizing our findings without further research, the scope of this paper might provide some direction for future studies of other organizations. We suggest that there is also a need to be open to methods which allow individuals and groups to define a climate of inclusivity that is relevant to their context; this is because context may be essential for recognizing certain groups of people.

BackgroundWearable devices can diagnose, monitor, and manage neurological disorders such as Parkinson disease. With a growing number of wearable devices, it is no longer a case of whether a wearable device can measure Parkinson disease motor symptoms, but rather which features suit the user. Concurrent with continued device development, it is important to generate insights on the nuanced needs of the user in the modern era of wearable device capabilities. ObjectiveThis study aims to understand the views and needs of people with Parkinson disease regarding wearable devices for disease monitoring and management. MethodsThis study used a mixed method parallel design, wherein survey and focus groups were concurrently conducted with people living with Parkinson disease in Munster, Ireland. Surveys and focus group schedules were developed with input from people with Parkinson disease. The survey included questions about technology use, wearable device knowledge, and Likert items about potential device features and capabilities. The focus group participants were purposively sampled for variation in age (all were aged >50 years) and sex. The discussions concerned user priorities, perceived benefits of wearable devices, and preferred features. Simple descriptive statistics represented the survey data. The focus groups analyzed common themes using a qualitative thematic approach. The survey and focus group analyses occurred separately, and results were evaluated using a narrative approach. ResultsOverall, 32 surveys were completed by individuals with Parkinson disease. Four semistructured focus groups were held with 24 people with Parkinson disease. Overall, the participants were positive about wearable devices and their perceived benefits in the management of symptoms, especially those of motor dexterity. Wearable devices should demonstrate clinical usefulness and be user-friendly and comfortable. Participants tended to see wearable devices mainly in providing data for health care professionals rather than providing feedback for themselves, although this was also important. Barriers to use included poor hand function, average technology confidence, and potential costs. It was felt that wearable device design that considered the user would ensure better compliance and adoption. ConclusionsWearable devices that allow remote monitoring and assessment could improve health care access for patients living remotely or are unable to travel. COVID-19 has increased the use of remotely delivered health care; therefore, future integration of technology with health care will be crucial. Wearable device designers should be aware of the variability in Parkinson disease symptoms and the unique needs of users. Special consideration should be given to Parkinson disease–related health barriers and the users’ confidence with technology. In this context, a user-centered design approach that includes people with Parkinson disease in the design of technology will likely be rewarded with improved user engagement and the adoption of and compliance with wearable devices, potentially leading to more accurate disease management, including self-management.

A battolyser is a combined battery electrolyser in one unit. It is based on flow battery technology and can be adapted to produce hydrogen at a lower efficiency than an electrolyser but without the need for rare and expensive materials. This paper presents a method of determining if a battolyser connected to a wind farm makes economic sense based on stochastic modelling. A range of cost data and operational scenarios are used to establish the impact on the NPV and LCOE of adding a battolyser to a wind farm. The results are compared to adding a battery or an electrolyser to a wind farm. Indications are that it makes economic sense to add a battolyser or battery to a wind farm to use any curtailed wind with calculated LCOE at £56/MWh to £58/MWh and positive NPV over a range of cost scenarios. However, electrolysers, are still too expensive to make economic sense.

Biomechanical analysis of gait is commonly used in physiotherapy. Ground reaction forces during phases of gait is one element of kinetic analysis. In this article, we analyze if the MoveSole® smart insole is valid and accurate equipment for measuring ground reaction forces in clinical physiotherapy. MoveSole® StepLab is a mobile measurement system for instant underfoot force measurements during gait. Unique electromagnetic film (EMFI) based sensor technology and printed electronics production technology is integrated in the MoveSole® StepLab measurement system. The MoveSole® StepLab measures plantar ground reaction force distribution over the sensors and provides an estimation of the maximum total ground reaction force. We developed a two phase validation process to extract relevant parameters and compared the results to a Kistler force plate using the BioWare® analyzing program as a reference method. Our results show that MoveSole® smart insoles reach the strong level of accuracy needed in clinical work concerning highest ground reaction forces during step (Pearson correlation .822 - .875). The correlation of the time when the maximum ground reaction force occurred was moderate, e.g. during heel strike or toe-off (Pearson correlation natural gait speed .351 - .462, maximum gait speed .430). Our conclusion is that MoveSole® smart insoles are a potential tool for analyzing and monitoring gait ground reaction forces during physiotherapy processes.

We report a case of partial diazoxide responsiveness in a child with severe congenital hyperinsulinaemic hypoglycaemia (CHI) due to a homozygous ABCC8 mutation. A term baby, with birth weight 3.8 kg, born to consanguineous parents presented on day 1 of life with hypoglycaemia. Hypoglycaemia screen confirmed CHI. Diazoxide was commenced on day 7 due to ongoing elevated glucose requirements (15 mg/kg/min), but despite escalation to a maximum dose (15 mg/kg/day), intravenous (i.v.) glucose requirement remained high (13 mg/kg/min). Genetic testing demonstrated a homozygous ABCC8 splicing mutation (c.2041-1G>C), consistent with a diffuse form of CHI. Diazoxide treatment was therefore stopped and subcutaneous (s.c.) octreotide infusion commenced. Despite this, s.c. glucagon and i.v. glucose were required to prevent hypoglycaemia. A trial of sirolimus and near-total pancreatectomy were considered, however due to the significant morbidity potentially associated with these, a further trial of diazoxide was commenced at 1.5 months of age. At a dose of 10 mg/kg/day of diazoxide and 40 μg/kg/day of octreotide, both i.v. glucose and s.c. glucagon were stopped as normoglycaemia was achieved. CHI due to homozygous ABCC8 mutation poses management difficulties if the somatostatin analogue octreotide is insufficient to prevent hypoglycaemia. Diazoxide unresponsiveness is often thought to be a hallmark of recessively inherited ABCC8 mutations. This patient was initially thought to be non-responsive, but this case highlights that a further trial of diazoxide is warranted, where other available treatments are associated with significant risk of morbidity.

This study explored the use of artificial neural networks in the estimation of runners' kinetics from lower body kinematics. Three supervised feed-forward artificial neural networks with one hidden layer each were modelled and assigned individually with the mapping of a single force component. Number of training epochs, batch size and dropout rate were treated as modelling hyper-parameters and their values were optimised with a grid search. A public data set of twenty-eight professional athletes containing running trails of different speeds (2.5 m/sec, 3.5 m/sec and 4.5 m/sec) was employed to train and validate the networks. Movements of the lower limbs were captured with twelve motion capture cameras and an instrumented dual-belt treadmill. The acceleration of the shanks was fed to the artificial neural networks and the estimated forces were compared to the kinetic recordings of the instrumented treadmill. Root mean square error was used to evaluate the performance of the models. Predictions were accompanied with low errors: 0.134 BW for the vertical, 0.041 BW for the anteroposterior and 0.042 BW for the mediolateral component of the force. Vertical and anteroposterior estimates were independent of running speed (p=0.233 and p=.058, respectively), while mediolateral results were significantly more accurate for low running speeds (p=0.010). The maximum force mean error between measured and estimated values was found during the vertical active peak (0.114 ± 0.088 BW). Findings indicate that artificial neural networks in conjunction with accelerometry may be used to compute three-dimensional ground reaction forces in running.

Abstract Background Slowing eating rate using the Mandolean® previously helped obese adolescents to self-select smaller portion sizes, with no reduction in satiety, and enhanced ghrelin suppression. The objective of this pilot, randomised trial was to investigate the neural response to food cues following Mandolean® training using functional Magnetic Resonance Imaging (fMRI), and measures of ghrelin, PYY, glucose and self-reported appetite. Method Twenty-four obese adolescents (11–18 years; BMI ≥ 95th centile) were randomised (but stratified by age and gender) to receive six-months of standard care in an obesity clinic, or standard care plus short-term Mandolean® training. Two fMRI sessions were conducted: at baseline and post-intervention. These sessions were structured as an oral glucose tolerance test, with food cue-reactivity fMRI, cannulation for blood samples, and appetite ratings taken at baseline, 30 (no fMRI), 60 and 90 min post-glucose. As this was a pilot trial, a conservative approach to the statistical analysis of the behavioural data used Cliff’s delta as a non-parametric measure of effect size between groups. fMRI data was analysed using non-parametric permutation analysis (RANDOMISE, FSL). Results Following Mandolean® training: (i) relatively less activation was seen in brain regions associated with food cue reactivity after glucose consumption compared to standard care group; (ii) 22% reduction in self-selected portion size was found with no reduction in post-meal satiety. However, usage of the Mandolean® by the young people involved was variable and considerably less than planned at the outset (on average, 28 meals with the Mandolean® over six-months). Conclusion This pilot trial provides preliminary evidence that Mandolean® training may be associated with changes in how food cues in the environment are processed, supporting previous studies showing a reduction in portion size with no reduction in satiety. In this regard, the study supports targeting eating behaviour in weight-management interventions in young people. However, given the variable usage of the Mandolean® during the trial, further work is required to design more engaging interventions reducing eating speed. Trial registration ISRCTN, ISRCTN84202126, retrospectively registered 22/02/2018.

Parkinson's disease (PD) is a progressive neurological disorder of the central nervous system that deteriorates motor functions, while it is also accompanied by a large diversity of non-motor symptoms such as cognitive impairment and mood changes, hallucinations, and sleep disturbance. Parkinsonism is evaluated during clinical examinations and appropriate medical treatments are directed towards alleviating symptoms. Tri-axial accelerometers, gyroscopes, and magnetometers could be adopted to support clinicians in the decision-making process by objectively quantifying the patient's condition. In this context, at-home data collections aim to capture motor function during daily living and unobstructedly assess the patients' status and the disease's symptoms for prolonged time periods. This review aims to collate existing literature on PD monitoring using inertial sensors while it focuses on papers with at least one free-living data capture unsupervised either directly or via videotapes. Twenty-four papers were selected at the end of the process: fourteen investigated gait impairments, eight of which focused on walking, three on turning, two on falls, and one on physical activity; ten articles on the other hand examined symptoms, including bradykinesia, tremor, dyskinesia, and motor state fluctuations in the on/off phenomenon. In summary, inertial sensors are capable of gathering data over a long period of time and have the potential to facilitate the monitoring of people with Parkinson's, providing relevant information about their motor status. Concerning gait impairments, kinematic parameters (such as duration of gait cycle, step length, and velocity) were typically used to discern PD from healthy subjects, whereas for symptoms' assessment, researchers were capable of achieving accuracies of over 90% in a free-living environment. Further investigations should be focused on the development of ad-hoc hardware and software capable of providing real-time feedback to clinicians and patients. In addition, features such as the wearability of the system and user comfort, set-up process, and instructions for use, need to be strongly considered in the development of wearable sensors for PD monitoring.

This Special Issue captures a significant portion of the current sensors research excellence in Ireland [...]

For the first time, this paper reports a smart museum archive box that features a fully integrated wireless powered temperature and humidity sensor. The smart archive box has been specifically developed for microclimate environmental monitoring of stored museum artifacts in cultural heritage applications. The developed sensor does not require a battery and is wirelessly powered using Near Field Communications (NFC). The proposed solution enables a convenient means for wireless sensing with the operator by simply placing a standard smartphone in close proximity to the cardboard archive box. Wireless sensing capability has the advantage of enabling long-term environmental monitoring of the contents of the archive box without having to move and open the box for reading or battery replacement. This contributes to a sustainable preventive conservation strategy and avoids the risk of exposing the contents to the external environment, which may result in degradation of the stored artifacts. In this work, a low-cost and fully integrated NFC sensor has been successfully developed and demonstrated. The developed sensor is capable of wirelessly measuring temperature and relative humidity with a mean error of 0.37 °C and ±0.35%, respectively. The design has also been optimized for low power operation with a measured peak DC power consumption of 900 μW while yielding a 4.5 cm wireless communication range. The power consumption of the NFC sensor is one of the lowest found in the literature. To the author’s knowledge, the NFC sensor proposed in this paper is the first reporting of a smart archive box that is wirelessly powered and uniquely integrated within a cardboard archive box.

Athletic performance, technique assessment, and injury prevention are all important aspects in sports for both professional and amateur athletes. Wearable technology is attracting the research community’s interest because of its capability to provide real-time biofeedback to coaches and athletes when on the field and outside of more restrictive laboratory conditions. In this paper, a novel wearable motion sensor-based system has been designed and developed for athletic performance assessment during running and jumping tasks. The system consists of a number of components involving embedded systems (hardware and software), back-end analytics, information and communications technology (ICT) platforms, and a graphical user interface for data visualization by the coach. The system is able to provide automatic activity recognition, estimation of running and jumping metrics, as well as vertical ground reaction force (GRF) predictions, with sufficient accuracy to provide valuable information as regards training outcomes. The developed system is low-power, sufficiently small for real-world scenarios, easy to use, and achieves the specified communication range. The system’s high sampling rate, levels of accuracy and performance enables it as a performance evaluation tool able to support coaches and athletes in their real-world practice.

The increased use of sensor technology has been crucial in releasing the potential for remote rehabilitation. However, it is vital that human factors, that have potential to affect real-world use, are fully considered before sensors are adopted into remote rehabilitation practice. The smart sensor devices for rehabilitation and connected health (SENDoc) project assesses the human factors associated with sensors for remote rehabilitation of elders in the Northern Periphery of Europe. This article conducts a literature review of human factors and puts forward an objective scoring system to evaluate the feasibility of balance assessment technology for adaption into remote rehabilitation settings. The main factors that must be considered are: Deployment constraints, usability, comfort and accuracy. This article shows that improving accuracy, reliability and validity is the main goal of research focusing on developing novel balance assessment technology. However, other aspects of usability related to human factors such as practicality, comfort and ease of use need further consideration by researchers to help advance the technology to a state where it can be applied in remote rehabilitation settings.

Wrist-worn activity trackers have experienced a tremendous growth lately and studies on the accuracy of mainstream trackers used by older adults are needed. This study explores the performance of six trackers (Fitbit Charge2, Garmin VivoSmart HR+, Philips Health Watch, Withings Pulse Ox, ActiGraph GT9X-BT, Omron HJ-72OITC) for estimating: steps, travelled distance, and heart-rate measurements for a cohort of older adults. Eighteen older adults completed a structured protocol involving walking tasks, simulated household activities, and sedentary activities. Less standardized activities were also included, such as: dusting, using a walking aid, or playing cards, in order to simulate real-life scenarios. Wrist-mounted and chest/waist-mounted devices were used. Gold-standards included treadmill, ECG-based chest strap, direct observation or video recording according to the activity and parameter. Every tracker showed a decreasing accuracy with slower walking speed, which resulted in a significant step under-counting. A large mean absolute percentage error (MAPE) was found for every monitor at slower walking speeds with the lowest reported MAPE at 2 km/h being 7.78%, increasing to 20.88% at 1.5 km/h, and 44.53% at 1 km/h. During household activities, the MAPE climbing up/down-stairs ranged from 8.38-19.3% and 10.06-19.01% (dominant and non-dominant arm), respectively. Waist-worn devices showed a more uniform performance. However, unstructured activities (e.g. dusting, playing cards), and using a walking aid represent a challenge for all wrist-worn trackers as evidenced by large MAPE (> 57.66% for dusting, > 67.32% when using a walking aid). Poor performance in travelled distance estimation was also evident during walking at low speeds and climbing up/down-stairs (MAPE > 71.44% and > 48.3%, respectively). Regarding heart-rate measurement, there was no significant difference (p-values > 0.05) in accuracy between trackers placed on the dominant or non-dominant arm. Concordant with existing literature, while the mean error was limited (between -3.57 bpm and 4.21 bpm), a single heart-rate measurement could be underestimated up to 30 beats-per-minute. This study showed a number of limitations of consumer-level wrist-based activity trackers for older adults. Therefore caution is required when used, in healthcare or in research settings, to measure activity in older adults.

Heat stress (HS) compromises productivity of pork production, in part as a result of increased oxidative stress and inflammatory responses, particularly within the gastrointestinal tract. This study aimed to investigate whether plant-derived betaine and isoquinoline alkaloids could ameliorate HS in pigs. Fifty female Large White × Landrace grower pigs, which were acclimated to control (CON), control plus betaine (BET), or control plus isoquinoline alkaloids (IQA) diets for 14 days were then exposed to heat stress or thermoneutral condition. Both BET and IQA partially ameliorated increases in respiration rate (p = 0.013) and rectal temperature (p = 0.001) associated with HS conditions. Heat stress increased salivary cortisol concentrations and reduced plasma creatinine, lactate, and thyroid hormone concentrations. Heat stress increased colon FD4 permeability, which was reduced by IQA (p = 0.030). Heat stress increased inflammation in the jejunum and ileum, as indicated by elevated interleukin-1β (p = 0.022) in the jejunum and interleukin-1β (p = 0.004) and interleukin-8 (p = 0.001) in the ileum. No differences in plasma total antioxidant capacity (TAC) were observed with HS, but betaine increased plasma TAC compared to IQA. Dietary BET increased betaine concentrations in the jejunum, ileum (p < 0.001 for both), plasma, liver, kidney (p < 0.010 for all), urine (p = 0.002) and tended to be higher in muscle (p = 0.084). Betaine concentration was not influenced by HS, but it tended to be higher in plasma and accumulated in the liver. These data suggest that betaine and isoquinoline alkaloids supplementation ameliorated consequences of heat stress in grower pigs and protected against HS induced increases in colonic permeability.