Abstract: Digital Sampling Oscilloscopes (DSOs) serve as crucial instruments for characterizing high-speed data signals. However, they encounter measurement uncertainties arising from various sources such as jitter and time distortions. To enhance sampling accuracy, this paper introduces a phase trigger sampling approach aimed at mitigating sampling jitter in DSOs through a clock phase shifting technique. We have developed and implemented a phase-trigger DSO utilizing FPGA technology, wherein a clock phase shifter chip replaces the conventional Phase Locked Loop (PLL) for generating sampling frequencies, addressing random jitter induced by phase fluctuations. Our proposed technique demonstrates a significant enhancement in measurement accuracy, with improvements around 50% observed depending on data rate and pattern length.

Abstract: Sleep disorders caused by snoring are a common problem that negatively affect the individual’s daily quality of life. For instance, poor sleep caused by snoring will induce important physical and mental issues. Given the fact that finding common criteria for all snoring sounds is very tough, this study aims to propose two models for snoring classification using AI-based learning methods. The first model is a Machine Learning (ML)-based built by stacking two classifiers namely, the SVM and KNN, that will learn the features extracted by applying the MFCC as a feature extraction technique. The second model is a Deep Learning (DL)-based where RNN and LSTM classifiers are stacked and where three feature extraction techniques (i.e. MFCC, STFT, ZCR) are applied. An online dataset consisting of .wav audio signals is used to implement the two models. Results show that the first and second models have achieved high accuracy scores of 98.5% and 80.8% respectively.

Abstract: Data privacy has become the center of attention to many researchers and engineers. With high speed data transmission, data privacy can be at risk. Data stream anonymization is a fairly new and effective technique that is being currently investigated. It aims to protect data from third-party attackers. A user must keep in mind that when applying anonymization on a dataset, there will be a tradeoff between data utility and the risk of data identification. I n this paper, w e propose various anonymization cores that can be used to hide the sensitive parts of the data. The hardware implementation on FPGA of these cores is also discussed. Each implementation takes into consideration the trade-off between the throughput and the power consumption in addition to the application type and specifications. The first architecture treats a simple application where two anonymization techniques are used (i.e. Perturbation and character masking). The second implementation requires more complex anonymization techniques and extends K-anonymity criteria and L-diversity for more sensitive applications where data identification is crucial. Results are compared with existing work implementations and many improvements are applied in terms of resource utilization and throughput.

Abstract: Sleep posture is a clinical relevant parameter for it is associated with several pathologies and affects the quality of sleep. In this paper, we propose SleepPal a sleep monitoring system for body movement and sleep posture detection. It consists of a wearable device that extracts data from a 3-axis accelerometer and transmits them to a remote monitoring station. A threshold-based algorithm is used to detect body movement and to distinguish between transitions. The proposed system will also evaluate the sleep quality index. Experiments were conducted on 10 subjects and results showed 88% of sensitivity and 82% of accuracy.

Abstract: In this paper we investigate implementing a Precision Time Base (PTB) technique to improve measurement jitter performance of digital sampling oscilloscopes (DSO) on a Field Programmable Gate Array (FPGA). To achieve better measurements, two reference signals are used to correct time-base errors and minimize jitter added by the DSO itself (minimize measurement jitter). We show experimentally that using the aforementioned technique, measurement jitter can be reduced from 1.3 pico-seconds (ps) to 280 femto-seconds (fs) (depending on the data rate and the pattern length) on a high-speed DSO.

Abstract: Falls in elderly are an important issue for the aging populations around the world. They cause severe physical and emotional injuries and surge healthcare and hospitalization costs. Detection of falls in time help reduce the consequences of the fall by providing a faster rescue to the patient which prevents more serious injuries. The present research describes a threshold-based algorithm to distinguish between falls and Activities of Daily Living (ADL). This algorithm was implemented on a wearable device attached to the waist. Three thresholds are used in order to distinguish a fall from any other activity. Falls are simulated by 10 young volunteers under supervised conditions and ADLs are performed by 10 elderly subjects. Experimental results show that the system detects falls compared to ADL with a sensitivity and specificity of 93.3% and 100% respectively.

Abstract: As people age, they become more fragile and exhibit changes in their gait and balance. This state of fragility increases their vulnerability to fall incidents. Gait and balance assessment is usually performed in a clinical setting primarily after a fall. However, daily monitoring has become essential in order to evaluate the quality of gait and alert the patient in case of a risky situation. In this context, many systems have been developed that allow the extraction of specific features in the purpose to detect or predict a fall during daily activities. Footwear systems have been of interest for being non-intrusive and adequate for everyday use. This paper describes the design and development of our proposed force-sensing shoe for gait analysis and monitoring. The system is validated by the extraction of the weight and the Center of Pressure (CoP) trajectory of 10 young volunteers. Results have shown that minor adjustment need to be performed to obtain accurate measurement of the weight. A final design with new features has been sent for manufacturing.

Abstract: Earth is known as the "Blue Planet". 70% of the earth's surface is covered with water. It has an abundance of water, but unfortunately, only a small proportion is available to humans. This resource, which becomes increasingly limited, is essential to life and an important component for the development of agriculture, energy production, industrial activities and domestic consumption. The needs are thus in a very fast growth. Against this reality, it falls to us to preserve this resource and to make the best possible use of it. In this context, solutions started to appear allowing more efficient management of water resources. This paper provides the implementation of a software solution that aims to reduce the domestic water consumption according the basic daily activities and needs. This management is in fact a control of the consumption by predicting the tasks which are allowed to satisfy by specifying the volumetric flow used. The system will help the users with decision making according to their needs and will enable them to satisfy a large number of daily tasks without excessive water use.

Abstract: As people age, they become more fragile and exhibit difficulties in maintaining their gait and balance. Their state of fragility increases their vulnerability to fall incidents. Various analysis methods were developed to detect the abnormality of human gait and balance, and estimate the risk of falling. In this paper, we present a method to estimate the falling risk and alert the patient when a fall is about to happen. The proposed method consists in monitoring and analyzing the amount of sway of the center of mass in the medial-lateral plane by computing the center of pressure displacement at the foot plantar surface. Our proposed method uses the spatio-temporal sliding window processing to generate fall alarms and estimate the falling risk. The method was validated via a two-phase experimental protocol with five young adults who performed a walk of 20 stances with simulated sways using an instrumented shoe with resistive pressure sensors. The threshold of the normal walk TH N and the risk level R L of the altered walk are determined as well as the risk of falling. The method can be applied in real-life and clinical settings with real-time processing.

Abstract: Visually Impaired (VI) and blind people suffer from reduced mobility, as they cannot detect the terrain and their environment. They always need assistance and walking support systems in their daily life. Solutions have been proposed many decades ago and are rapidly improving nowadays due to the technology evolution and integration. A large number of assistance aids have been deployed in real life situations whereas other concepts remained as research ideas. This paper describes a new approach of an ambient navigation system that would help the visually impaired or blind person to move freely indoor (house, office, etc.) without the assistance of anyone. The system is composed of IP cameras attached to the ceiling of each room and the smart phone of the subject is used as human machine interface (HMI). Frames are sent to a computer that analyzes the environment, detects and recognizes objects. A computer vision guidance algorithm is designed to help the user reach his destination (or his personal item) with obstacle detection. The system is commanded by voice messages via a simple mobile application. Feedbacks (alerts, route) are voice messages returns by the application to the user. This system provides a reliable solution to assist those users in their indoor navigation providing them a correct route with obstacle avoidance.

Abstract: Software keyboards were designed to provide accessibility to mobile users as well as to people with motor disability. Text entry is henceforth made possible on portable devices such as mobile phones, tablets, pads. Despite their obvious utility, these keyboards present major drawbacks in terms of speed of acquisition and induced fatigue comparatively to conventional physical keyboards. Optimization efforts have showed efficacy by adding prediction lists and dictionaries. Other researches have considered the effect of the position of characters and the prediction list relatively to the time of acquisition and performance. Those researches were designed for computer software keyboards. In this paper, the position of the prediction list is investigated on a mobile device. The “MobiCentraList” is the mobile version of a previous computer software keyboard “Centralist” which was developed for this purpose. The position effect of the prediction list is studied and compared to natural software keyboards.

Abstract: Falls are events that affect almost every aging human being above the age of 65. These incidents can have major consequences on the physiological, psychological and socio-economical levels. In this paper, a simple smart carpet design is developed to detect falls using a novel sensing technique. Conventional sensing methods use either inertial measurement sensors (accelerometers, gyroscopes) or environmental sensors (infrared, force, vibration, acoustic, etc.). The proposed technique employs differential piezoresistive pressure sensors. The prototype of the system is implemented and tested using statistical methods. Experimental results show the sensitivity and the specificity of the system to be 88.8% and 94.9% respectively. The system could be deployed in home care environment as a final product. Our proposed sensing technique can be also integrated in beds to alert patients from falling during sleep.

Abstract: Visual impairment or vision loss is the main reason for reduced mobility in humans. Visually Impaired (VI) people require continuous assistance during their movement. Researchers and scientists have put many solutions to assist those people in the activities of their daily living (ADL). The current research delivers a novel indoor navigation system for visually impaired people. The proposed solution is designed for indoor use only (house, office, companies, etc.). It provides the visually impaired person the ability to navigate without any other hardware assistance. The proposed system architecture uses a network of IP cameras installed at the ceiling of each room. A remote processing system analyzes-by computer vision algorithms-photos taken from the environment in order to inform the subject about his location and reacts accordingly to deliver the adequate assistance. A guidance algorithm helps him reach his destination using a simple interactive mobile application installed on his smart phone. The proof of concept prototype was designed with one camera on top of a wooden floor model to simulate the system. Results showed good reliability in indoor navigation and obstacles avoidance.

Abstract: Assisted living for people with disabilities remains a current research challenge. Many systems have been developed to help disabled and frail people gain their self-sufficiency during their activities of daily living (ADL). In this article, we propose a new design concept to help visually impaired (VI) elderly patients move in their home environment. The system is made of a light-weight medical walker where sensory components and processing electronics are installed and operated. Behavioral and environmental information are collected using proper sensors mounted on walker's frame. Direction data are provided using audible notification. The system uses a hardware guiding technique based on ultrasonic and optical sensors for obstacle detection and accelerometer for fall and vibration detection. The algorithm developed for this purpose triggers an audible notification to alert the patient if there is an obstacle ahead. While many developed walkers are complex, expensive and require training to be used, our electronic walker gathers flexibility, reliability, ease of use and future expendability. Unlike other products, the electronic walker is also suitable for indoor and outdoor use. The results obtained after testing the system proved effectiveness. The use of low cost components makes our walker affordable as a final product.

Abstract: Renewable energy and cogeneration systems integration into a grid has become an important issue for the power generation management. In this work, a new algorithm is proposed to manage the power generation. This algorithm takes into account the electrical and thermal load demands and the instantaneous renewable energy generation and cogeneration integration into a grid. In addition, the conventional power generators and cogeneration systems will be selected optimally according to economic and environmental criteria, and automated through microcontrollers. The reduced cost and pollution due to the integration of renewable energy and cogeneration sources are then calculated for decision making reasons.