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IoT-Based Deep Neural Network Approach for Heart Rate and SpO2 Prediction
Published in K. Gayathri Devi, Kishore Balasubramanian, Le Anh Ngoc, Machine Learning and Deep Learning Techniques for Medical Science, 2022
Madhusudan G. Lanjewar, Rajesh K. Parate, Rupesh D. Wakodikar, Anil J. Thusoo
The proposed DNN-based system has been implemented on the Raspberry pi-4 board is shown in Figure 7.1. Raspberry pi has the features of the I2C interface to attach the sensor. One sensor is used, which is compatible with the Raspberry pi is employed to detect the parameters like HR and SpO2. Sensor interfaced with Raspberry pi through General Purpose Input/output (GPIO) pins. Sensor output is given to the PCA algorithm. PCA is usually transforming a large dataset into a smaller dataset by reducing the dimension [35]. The Performance of ML or DL can be improved using PCA [36]. The PCA data and corresponding output data are used to train the model. Now, the trained DNN model is prepared to predict the HR and SpO2. Raspberry pi again reads the sensor data and passes it to the PCA algorithm. The PCA data unknown to the DNN model is given to the trained DNN model for prediction. The system sends the predicted values to the OLED display, to the cloud for future use, and sent to WhatsApp and SMS to the patient or concerned person's mobile number through the cloud.
Power Management IC Design for Efficient DVFS-Enabled On-Chip Operations
Published in Iniewski Krzysztof, Integrated Microsystems, 2017
SIMO converters have been researched considerably, leading to novel control schemes, which are applied for numerous advanced applications. Recently, a SIMO DC–DC converter was presented, which employed an ordered power-distributive control [26]. This converter regulates four main positive boost outputs and one dependent negative output developed by a CP. The design in [27] presents a SIDO DC–DC buck converter design, which shares the magnetic energy stored in the inductor to simultaneously power two independent loads. This converter uses a modified PWM control strategy for output voltage regulation, while dynamically biasing the power transistors’ substrate voltages. The TPS65120 SIMO converter presented in [28] is a commercial product, which is designed to offer a power supply solution for small-form-factor thin-film transistor (TFT) LCD panels. The control technique employs two regulation loops, with the first managed through a state machine. The first loop controls the switching actions of the power stage, while the second loop employs a variable peak current control technique for minimizing the inductor current. Finally, the design in [29] proposes a SIMO step-up converter with bipolar outputs, specifically designed for active matrix organic light-emitting diode (OLED) mobile display panels. The positive output voltage is controlled using a modified comparator control technique, while the negative output is regulated using a charge-pump operation with proportional-integral control.
Pervasive Computing and Ambient Physiological Monitoring Devices
Published in Bruno Bouchard, Smart Technologies in Healthcare, 2017
Sung Jae Isaac Chang, Jennifer Boger, Jianfeng Qiu, Alex Mihailidis
One of the areas that ambient physiological monitoring is expected to improve is its usability and unobtrusiveness through the incorporation of progressively advanced sensors. Hard electronic components that are currently used, such as the photodiode and LED light used for PPG, will be replaced with flexible sensors to increase the blending of the sensors into the furniture. Although the flexible sensors, such as electromechanical film (EMFi) does not interfere with a user’s activites, its unobtrusiveness can be improved by using newly developed sensors to make the sensor- furniture assembly completely seamless and blended. Examples of the newly emerging sensors include flexible photo-transistor and organic light emitting diode (OLED) for PPG sensing (Chang et al. 2013; Lee et al. 2014) and carbon nanotube (CNT)-based flexible film strain sensors for BCG and respiration sensing. CNTs can measure strain 50 times greater than the conventional strain gauge being incorporated into a fabric (Yamada et al. 2011). However, these sensors are still in development stage and need to be proven as durable and reliable prior to being incorporated in a consumer- ready product (Zheng et al. 2014).
Hydrogels for localized chemotherapy of liver cancer: a possible strategy for improved and safe liver cancer treatment
Published in Drug Delivery, 2022
Jianyong Ma, Bingzhu Wang, Haibin Shao, Songou Zhang, Xiaozhen Chen, Feize Li, Wenqing Liang
Hydrogels are large polymeric networks that are highly magnified, hydrophilic, and capable of retaining a large amount of water within their pores (Martin & Youssef, 2018; Wang, 2018). Due to their enhanced biocompatibility, these bioactive resources are commonly used in tissue engineering (Vermonden & Klumperman, 2015). Hydrogels have a porous structure and soft surface and behave similarly to natural living tissues. Owing to various stimuli-responsive potential to temperature, pH, pressure, electric and magnetic fields, these hydrogels are undoubtedly referred to as smart materials. Even at a slight pH change in the swelling medium, these materials have a high potential for proton release and uptake (Liu et al., 2015). The above mention characteristic of hydrogels makes them able to be served as an effective drug delivery vehicle. Literature has demonstrated the remarkable contributions of multi-responsive hydrogels such as polyvinyl alcohol crosslinked polyacrylamide and poly(N-isopropylacrylamide) (PNIPAM)/CTS as smart sensors, effectors, and targeted delivery to tumor cells (Liu et al., 2017; Manga & Jha, 2017). Polymeric hydrogels such as CTS and keratin (polylactic keratin) are extensively studied for their potential use in the fabrication of LCD (liquid crystal display) and OLED (organic light-emitting diode) materials, as well as specific drug delivery systems (Karimi et al., 2017).
Predictive analysis for joint progressive censoring plans: a Bayesian approach
Published in Journal of Applied Statistics, 2022
Mohammad Vali Ahmadi, Mahdi Doostparast
For assessing the life information of the white organic light-emitting diode (OLED), Zhang et al. [26] considered two samples of sizes m = 10 and n = 8 on failure times of OLED products recorded at two different levels of stress are analyzed. The failure times (in hours) corresponding to these two samples, denoted by X and Y, are reported in Table 7. For answering the question whether the exponential distribution is appropriate for these two samples or not, we use the Shapiro-Wilk (S-W) goodness of fit test. Since the S-W distances for these two samples are 0.9268 and 0.9147 with corresponding p-values as 0.4176 and 0.3887, respectively, we accept that the exponential distribution provides a good fit to these data.
The challenge of reading music notation for pianists with low vision: An exploratory qualitative study using a head-mounted display
Published in Assistive Technology, 2022
Bianka Lussier-Dalpé, Catherine Houtekier, Josée Duquette, Marie-Chantal Wanet-Defalque, Walter Wittich
The technical specifications for eSight Eyewear have previously been presented in more detail (Wittich et al., 2018). The study device was a second-generation device with a high-definition camera and two Organic Light Emitting Diode (OLED) screens mounted on a frame that is comparable to a pair of fully-enclosing sunglasses. The remote control contains the processor and the battery. Magnification factors range from 1.3 X to 12.3 X (21.2 to 2.3 degrees horizontal field) (Wittich et al., 2018), the automatic fine-tuning takes place in real time and this HMD offers magnification at near (from 30 cm) as well as intermediate and distance vision. The user’s prescription can be integrated into the device. The screens are positioned in immersive view or are inclined to occupy only the upper part of the visual field (VF). Even though users benefit from magnification immediately when wearing the device, to optimally operate it and master its use may take several months. To this end, eSight Corporation has developed eSkills, a program for developing the required visual skills (eSight Corporation, 2015).