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Individuals who are unable to walk independently spend most of the day in a wheelchair. This population is at high risk for developing pressure injuries caused by sitting. However, early diagnosis and prevention of these injuries still remain challenging. Herein, we introduce battery-free, wireless, multimodal sensors and a movable system for continuous measurement of pressure, temperature, and hydration at skin interfaces. The device design includes a crack-activated pressure sensor with nanoscale encapsulations for enhanced sensitivity, a temperature sensor for measuring skin temperature, and a galvanic skin response sensor for measuring skin hydration levels. The movable system enables power harvesting, and data communication to multiple wireless devices mounted at skin-cushion interfaces of wheelchair users over full body coverage. Experimental evaluations and numerical simulations of the devices, together with clinical trials for wheelchair patients, demonstrate the feasibility and stability of the sensor system for preventing pressure injuries caused by sitting.

Surface ozone is one of six air pollutants designated as harmful by National Ambient Air Quality Standards because it can adversely impact human health and the environment. Thus, ozone forecasting is a critical task that can help people avoid dangerously high ozone concentrations. Conventional numerical approaches, as well as data-driven forecasting approaches, have been studied for ozone forecasting. Data-driven forecasting models, in particular, have gained momentum with the introduction of machine learning advancements. We consider planetary boundary layer (PBL) height as a new input feature for data-driven ozone forecasting models. PBL has been shown to impact ozone concentrations, making it an important factor in ozone forecasts. In this paper, we investigate the effectiveness of utilization of PBL height on the performance of surface ozone forecasts. We present both surface ozone forecasting models, based on multilayer perceptron (MLP) and bidirectional long short-term memory (LSTM) models. These two models forecast hourly ozone concentrations for an upcoming 24-h period using two types of input data, such as measurement data and PBL height. We consider the predicted values of PBL height obtained from the weather research and forecasting (WRF) model, since it is difficult to gather actual PBL measurements. We evaluate two ozone forecasting models in terms of index of agreement (IOA), mean absolute error (MAE), and root mean square error (RMSE). Results showed that the MLP-based and bidirectional LSTM-based models yielded lower MAE and RMSE when considering forecasted PBL height, but there was no significant changes in IOA when compared with models in which no forecasted PBL data were used. This result suggests that utilizing forecasted PBL height can improve the forecasting performance of data-driven prediction models for surface ozone concentrations.

Capabilities for continuous monitoring of pressures and temperatures at critical skin interfaces can help to guide care strategies that minimize the potential for pressure injuries in hospitalized patients or in individuals confined to the bed. This paper introduces a soft, skin-mountable class of sensor system for this purpose. The design includes a pressure-responsive element based on membrane deflection and a battery-free, wireless mode of operation capable of multi-site measurements at strategic locations across the body. Such devices yield continuous, simultaneous readings of pressure and temperature in a sequential readout scheme from a pair of primary antennas mounted under the bedding and connected to a wireless reader and a multiplexer located at the bedside. Experimental evaluation of the sensor and the complete system includes benchtop measurements and numerical simulations of the key features. Clinical trials involving two hemiplegic patients and a tetraplegic patient demonstrate the feasibility, functionality and long-term stability of this technology in operating hospital settings.

Repositioning is a common guideline for the prevention of pressure injuries of bedridden or wheelchair patients. However, frequent repositioning could deteriorate the quality of patient's life and induce secondary injuries. This paper introduces a method for continuous multi-site monitoring of pressure and temperature distribution from strategically deployed sensor arrays at skin interfaces via battery-free, wireless ionic liquid pressure sensors. The wirelessly delivered power enables stable operation of the ionic liquid pressure sensor, which shows enhanced sensitivity, negligible hysteresis, high linearity and cyclic stability over relevant pressure range. The experimental investigations of the wireless devices, verified by numerical simulation of the key responses, support capabilities for real-time, continuous, long-term monitoring of the pressure and temperature distribution from multiple sensor arrays. Clinical trials on two hemiplegic patients confined on bed or wheelchair integrated with the system demonstrate the feasibility of sensor arrays for a decrease in pressure and temperature distribution under minimal repositioning.

Capabilities for continuous monitoring of pressures and temperatures at critical skin interfaces can help to guide care strategies that minimize the potential for pressure injuries in hospitalized patients or in individuals confined to the bed. This paper introduces a soft, skin-mountable class of sensor system for this purpose. The design includes a pressure-responsive element based on membrane deflection and a battery-free, wireless mode of operation capable of multi-site measurements at strategic locations across the body. Such devices yield continuous, simultaneous readings of pressure and temperature in a sequential readout scheme from a pair of primary antennas mounted under the bedding and connected to a wireless reader and a multiplexer located at the bedside. Experimental evaluation of the sensor and the complete system includes benchtop measurements and numerical simulations of the key features. Clinical trials involving two hemiplegic patients and a tetraplegic patient demonstrate the feasibility, functionality and long-term stability of this technology in operating hospital settings., Uninterrupted monitoring of pressure and temperature at skin interfaces can help to minimize the potential for pressure injuries in hospitalized or bedridden patients. Here, the authors introduce a soft, skin-mountable sensor that can continuously provide readings via antennas mounted under bedding, and demonstrate the functionality and robustness of the devices on patients.

In this paper, we consider an electric vehicle (EV) charging schedule together with appliance scheduling in a residence under a day-ahead real-time pricing scheme (DA-RTP). Among demand response (DR) programs, EVs are an important resource for reducing energy cost due to high flexibility in energy scheduling. On the other hand, the required amount of energy to charge an EV has a counter effect on cost reduction. In a scheduling problem, a constraint on state-of-charge (SoC) of an EV when departing could be a factor in increased cost. Thus, instead of the constraint, we introduce a dissatisfaction at SoC when departing in the objective of the scheduling problem. We formulate our scheduling problem for minimizing a consumer's total dissatisfaction as a mixed-integer nonlinear programming (MINLP) problem since we consider shiftable but uninterruptible loads, which need an On/Off decision. We adopt an outer approximation algorithm to efficiently obtain an optimal solution.