Data Acquisition Devices Towards a System for Monitoring Sensory Processing Disorders

Abstract

People with autism spectrum disorder (ASD) manifest great heterogeneity in their atypical sensory behaviors. It is estimated that 95% of people with ASD have a Sensory Process Disorder (SPD). People with ASD feel the need to control what happens in their environment. However, it is inevitable that new situations occur during a person's daily life. Therefore, it is important to monitor most of the circumstances they face in an attempt to predict the appearance of disorders that end up affecting their behavior. This paper presents the first steps towards the development of a system for knowing the value and effect on the SPD of different biological and environmental parameters. To obtain those variables, two electronic devices have been designed. The first one is an electronic system for capturing environmental variables such as luminosity or humidity, which is portable and mobile. The second electronic device is a soft wearable wristband which gets biological parameters. To know the effect of those variables on the SPD, a complete software platform has been implemented. Both devices upload day-today data to a cloud database where the information is stored in timeseries data of different parameters. The system uses the data to learn a personalized model that is designed to manage the SPD of the user. The main novelty is the use of sensor integration, data processing and machine learning techniques to develop a system able to classify the sensory load supported by a user with ASD while performing different activities. The results obtained so far prove the feasibility of the approach.

Intelligent Monitoring Platform to Evaluate the Overall State of People with Neurological Disorders

“…The environmental and personal monitoring devices are responsible for measuring the environmental conditions and the user's physiological variables, respectively. The development of these devices, which are integrated within the presented platform in this work, along with a study of the different parameters measured by this data acquisition system is described in [15].…”

“…The personal monitoring device is the one described in [15], which integrates the measurement of the heart rate and the body temperature of the user. To complement the device, a new sensor has been integrated.…”

“…On the other hand, the management of these monitoring devices is done with a smartphone via an Android application. The application, also described in [15], also allows displaying information to the user or to the caregiver. The interface and the displayed information can be modified depending on the user and the corresponding application.…”

“…The interface and the displayed information can be modified depending on the user and the corresponding application. Furthermore, as described in [15], the smartphone also acts as a sound sensor, capturing the entire human audible spectrum (between 20 Hz and 22 kHz).…”

Design of System‐of‐System Acquisition Analysis Using Machine Learning

“…rough the use of collected and previously used data, predictive data analytics may foresee and forecast future consequences [4]. In Babylonian times, data was stored on tablets to anticipate harvest, but a dramatic leap in the ability to reason over enormous volumes of data arose in the 1940s with the advent of computer development [5,6], storage, and machine learning techniques [7]. In the 1940s and 1950s, data analytics models were utilised to anticipate the consequences of nuclear chain reactions in the Manhattan Project and weather forecasts using the ENIAC computer [8].…”