BackgroundOcclusions of intravenous (IV) tubing can prevent vital and time-critical medication or solutions from being delivered into the bloodstream of patients receiving IV therapy. At low flow rates (≤ 1 ml/h) the alarm delay (time to an alert to the user) can be up to 2 h using conventional pressure threshold algorithms. In order to reduce alarm delays we developed and evaluated the performance of two new real-time occlusion detection algorithms and one co-occlusion detector that determines the correlation in trends in pressure changes for multiple pumps.MethodsBench-tested experimental runs were recorded in triplicate at rates of 1, 2, 4, 8, 16, and 32 ml/h. Each run consisted of 10 min of non-occluded infusion followed by a period of occluded infusion of 10 min or until a conventional occlusion alarm at 400 mmHg occurred. The first algorithm based on binary logistic regression attempts to detect occlusions based on the pump’s administration rate Q(t) and pressure sensor readings P(t). The second algorithm continuously monitored whether the actual variation in the pressure exceeded a threshold of 2 standard deviations (SD) above the baseline pressure. When a pump detected an occlusion using the SD algorithm, a third algorithm correlated the pressures of multiple pumps to detect the presence of a shared occlusion. The algorithms were evaluated using 6 bench-tested baseline single-pump occlusion scenarios, 9 single-pump validation scenarios and 7 multi-pump co-occlusion scenarios (i.e. with flow rates of 1 + 1, 1 + 2, 1 + 4, 1 + 8, 1 + 16, and 1 + 32 ml/h respectively). Alarm delay was the primary performance measure.ResultsIn the baseline single-pump occlusion scenarios, the overall mean ± SD alarm delay of the regression and SD algorithms were 1.8 ± 0.8 min and 0.4 ± 0.2 min, respectively. Compared to the delay of the conventional alarm this corresponds to a mean time reduction of 76% (P = 0.003) and 95% (P = 0.001), respectively. In the validation scenarios the overall mean ± SD alarm delay of the regression and SD algorithms were respectively 1.8 ± 1.6 min and 0.3 ± 0.2 min, corresponding to a mean time reduction of 77% and 95%. In the multi-pump scenarios a correlation > 0.8 between multiple pump pressures after initial occlusion detection by the SD algorithm had a mean ± SD alarm delay of 0.4 ± 0.2 min. In 2 out of the 9 validation scenarios an occlusion was not detected by the regression algorithm before a conventional occlusion alarm occurred. Otherwise no occlusions were missed.ConclusionsIn single pumps, both the regression and SD algorithm considerably reduced alarm delay compared to conventional pressure limit-based detection. The SD algorithm appeared to be more robust than the regression algorithm. For multiple pumps the correlation algorithm reliably detected co-occlusions. The latter may be used to localize the segment of tubing in which the occlusion occurs.
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With the increased adoption of real-time objective measurements of player experience, advances have been made in characterising the dynamically changing aspects of the player experience during gameplay itself. A direct coupling to player action, however, is not without challenges. Many physiological responses, for instance, have an inherent delay, and often take some time to return to a baseline, providing challenges of interpretation when analysing rapidly changing gameplay on a micro level of interaction. The development of event-related, or phasic, measurements directly coupled to player actions provides additional insights, for instance through player modelling, but also through the use of behavioural characteristics of the human computer interaction itself. In this study, we focused on the latter, and measured keyboard pressure in a number of different, fast-paced action games. In this particular case, we related specific functional game actions (keyboard presses) to experiential player behaviour. We found keyboard pressure to be higher for avoidance as compared to approach-oriented actions. Additionally, the difference between avoidance and approach keyboard pressure related to levels of arousal. The findings illustrate the application potential of qualifying players’ functional actions at play (navigating in a game) and interpret player experience related to these actions through players’ real world behavioural characteristics like interface pressure.
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Background: The transformation in global demography and the shortage of health care workers require innovation and efficiency in the field of health care. Digital technology can help improve the efficiency of health care. The Mercury Advance SMARTcare solution is an example of digital technology. The system is connected to a hybrid mattress and is able to detect patient movement, based on which the air pump either starts automatically or sends a notification to the app. Barriers to the adoption of the system are unknown, and it is unclear if the solution will be able to support health care workers in their work. Objective: This study aims to gain insight into health care workers’ expectations of factors that could either hamper or support the adoption of the Mercury Advance SMARTcare unit connected to a Mercury Advance mattress to help prevent patients from developing pressure injuries in hospitals and long-term care facilities. Methods: We conducted a generic qualitative study from February to December 2022. Interviews were conducted, and a focus group was established using an interview guide of health care workers from both the United Kingdom and the Netherlands. Thematic analysis was performed by 2 independent researchers. Results: A total of 14 participants took part in the study: 6 (43%) participants joined the focus group, and 8 (57%) participants took part in the individual interviews. We identified 13 factors based on four themes: (1) factors specifically related to SMARTresponse, (2) vision on innovation, (3) match with health care activities, and (4) materials and resources involved. Signaling function, SMARTresponse as prevention, patient category, representatives, and implementation strategy were identified as facilitators. Perception of patient repositioning, accessibility to pressure injury aids, and connectivity were identified as barriers. Conclusions: Several conditions must be met to enhance the adoption of the Mercury Advance SMARTcare solution, including the engagement of representatives during training and a reliable wireless network. The identified factors can be used to facilitate the implementation process. JMIR Nursing 2024;7:e47992
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From Springer description: "We present the design considerations of an autonomous wireless sensor and discuss the fabrication and testing of the various components including the energy harvester, the active sensing devices and the power management and sensor interface circuits. A common materials platform, namely, nanowires, enables us to fabricate state-of-the-art components at reduced volume and show chemical sensing within the available energy budget. We demonstrate a photovoltaic mini-module made of silicon nanowire solar cells, each of 0.5 mm2 area, which delivers a power of 260 μW and an open circuit voltage of 2 V at one sun illumination. Using nanowire platforms two sensing applications are presented. Combining functionalised suspended Si nanowires with a novel microfluidic fluid delivery system, fully integrated microfluidic–sensor devices are examined as sensors for streptavidin and pH, whereas, using a microchip modified with Pd nanowires provides a power efficient and fast early hydrogen gas detection method. Finally, an ultra-low power, efficient solar energy harvesting and sensing microsystem augmented with a 6 mAh rechargeable battery allows for less than 20 μW power consumption and 425 h sensor operation even without energy harvesting."
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The Amsterdam Sensor Lab is part of the Amsterdam University of Applied Sciences (AUAS) and its goal is to develop application specific sensor systems for applied research. In order to (anonymously) measure, for instance, traffic without influencing people’s behaviour, a pressure sensing sub-tile is under development. It can be placed under a regular (0.3*0.3 m) tile in the pavement and, hence, cannot be seen by the public. Applications may range from evaluating the behaviour of pedestrians in crowds or on large open areas, to measuring the mechanical stress on bridges due to lorry traffic. The resulting data may be valuable to social scientists and municipal decision makers.A preliminary demonstration model has been realized that can detect: weight (pressure), direction, and a speed estimate of pedestrians and cyclists, by measuring the direction and velocity of pressure changes. Data communication is wireless, e.g., via Bluetooth™, to a Raspberry Pi™ or computer for calibration and visualization of the data. The demonstration model has been working satisfactorily for about half a year in the corridors of the AUAS.Pressure changes are measured with strain gauges using low-noise analogue instrumentation amplifiers and digitized with a 16 bit effective resolution. Current consumption is about 50 mA, the minimal detectable pressure is ca. 10 N and the maximal pressure ca. 1500 N. The data is refreshed every 2 ms.New electronics for a second version of the sub-tile (under development) make it possible to detect the tiny signal of a 0.3 gram rubber object falling from a 10 cm height. Investigations and development are going on to increase the measurement range from this low-level (impulse) pressure up to a pressure of about 500 kN, and configuring multiple sub-tiles to a wireless sensor network, thus paving the way to a (smart) sensing pavement. Apart from that, possibilities to give an estimate of the kind of traffic using artificial intelligence will be investigated.
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In this paper, we present a framework for gamified motor learning through the use of a serious game and high-fidelity motion capture sensors. Our implementation features an Inertial Measurement Unit and a set of Force Plates in order to obtain real-time, high-frequency measurements of patients' core movements and centre of pressure displacement during physical rehabilitation sessions. The aforementioned signals enable two mechanisms, namely a) a game avatar controlled through patient motor skills and b) a rich data stream for post-game motor performance analysis. Our main contribution is a fine-grained processing pipeline for sensor signals, enabling the extraction of a reliable and accurate mapping between patient motor movements, in-game avatar controls and overall motor performance. Moreover, we discuss the potential of this framework towards the implementation of personalised therapeutic sessions and present a pilot study conducted in that direction.
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Recent years have seen a global rise in the failure of tailings dams. Studies investigating the causes of slope failure often recognise high intensity rainfall events to significantly contribute to liquefaction, erosion and overtopping. This study aims to investigate the influence of alternative physical and geohydrological processes that, under tension saturation conditions, contribute to slope instability in tailings dams. It has been suggested that the generation of transient pressure wave mechanisms by high intensity rainfall events, surface ponding and wetting front advancement result in the formation of an induced pressure head that triggers the mobilization of pre-event water. In order to quantify these physical processes, this study included the analysis of rapid transmission conditions in a silica fines mix, with similar physical and hydraulic characteristics as platinum tailings. A tall leak-proof soil column, containing the soil sample compacted to in-situ dry bulk density, was fitted with seven observation ports. Each port consisted of a pore air pressure probe, a mini tensiometer and a time domain reflectometry probe. After set-up and initial stabilisation, three separate artificial high intensity rainfall events were applied to the surface. Monitoring of hydraulic state variables was recorded at thirty second intervals by automatic logging, thereby enabling the analysis of measured outcomes. Observations showed instant spikes in pore air pressure ahead of the wetting front, as well as a number of delayed responses. The interpretation of lab results led to the conclusion that pressure diffusion mechanisms throughout the porous medium, could result in the rapid release and mobilisation of previously stagnant antecedent moisture, thereby enabling phreatic levels to rising rapidly and in excess to the amount of surface infiltration. Also, since an increase in pore water pressure is likely to cause a reduction in shear strength, it is suggested that these physical and geohydrological processes could have an adverse impact on the stability of tailings dams.
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Light scattering is a fundamental property that can be exploited to create essential devices such as particle analysers. The most common particle size analyser relies on measuring the angle-dependent diffracted light from a sample illuminated by a laser beam. Compared to other non-light-based counterparts, such a laser diffraction scheme offers precision, but it does so at the expense of size, complexity and cost. In this paper, we introduce the concept of a new particle size analyser in a collimated beam configuration using a consumer electronic camera and machine learning. The key novelty is a small form factor angular spatial filter that allows for the collection of light scattered by the particles up to predefined discrete angles. The filter is combined with a light-emitting diode and a complementary metal-oxide-semiconductor image sensor array to acquire angularly resolved scattering images. From these images, a machine learning model predicts the volume median diameter of the particles. To validate the proposed device, glass beads with diameters ranging from 13 to 125 µm were measured in suspension at several concentrations. We were able to correct for multiple scattering effects and predict the particle size with mean absolute percentage errors of 5.09% and 2.5% for the cases without and with concentration as an input parameter, respectively. When only spherical particles were analysed, the former error was significantly reduced (0.72%). Given that it is compact (on the order of ten cm) and built with low-cost consumer electronics, the newly designed particle size analyser has significant potential for use outside a standard laboratory, for example, in online and in-line industrial process monitoring.
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Background Several footwear design characteristics are known to have detrimental effects on the foot. However, one characteristic that has received relatively little attention is the point where the sole flexes in the sagittal plane. Several footwear assessment forms assume that this should ideally be located directly under the metarsophalangeal joints (MTPJs), but this has not been directly evaluated. The aim of this study was therefore to assess the influence on plantar loading of different locations of the shoe sole flexion point. Method Twenty-one asymptomatic females with normal foot posture participated. Standardised shoes were incised directly underneath the metatarsophalangeal joints, proximal to the MTPJs or underneath the midfoot. The participants walked in a randomised sequence of the three shoes whilst plantar loading patterns were obtained using the Pedar® in-shoe pressure measurement system. The foot was divided into nine anatomically important masks, and peak pressure (PP), contact time (CT) and pressure time integral (PTI) were determined. A ratio of PP and PTI between MTPJ2-3/MTPJ1 was also calculated. Results Wearing the shoe with the sole flexion point located proximal to the MTPJs resulted in increased PP under MTPJ 4–5 (6.2%) and decreased PP under the medial midfoot compared to the sub-MTPJ flexion point (−8.4%). Wearing the shoe with the sole flexion point located under the midfoot resulted in decreased PP, CT and PTI in the medial and lateral hindfoot (PP: −4.2% and −5.1%, CT: −3.4% and −6.6%, PTI: −6.9% and −5.7%) and medial midfoot (PP: −5.9% CT: −2.9% PTI: −12.2%) compared to the other two shoes. Conclusion The findings of this study indicate that the location of the sole flexion point of the shoe influences plantar loading patterns during gait. Specifically, shoes with a sole flexion point located under the midfoot significantly decrease the magnitude and duration of loading under the midfoot and hindfoot, which may be indicative of an earlier heel lift.
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In wheelchair rugby (WR) athletes with tetraplegia, wheelchair performance may be impaired due to (partial) loss of innervation of upper extremity and trunk muscles, and low blood pressure (BP). The objective was to assess the effects of electrical stimulation (ES)-induced co-contraction of trunk muscles on trunk stability, arm force/power, BP, and WR performance.
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