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The heart of the project is the early and cost-effective diagnosis of impulse control disorders in children and adolescents. The methodology is based on the automatic analysis of speech and sleep patterns, which is being carried out in cooperation with Colombian and German partners. The group has set itself three project goals. In the first step, the synchronization of ongoing project work will be carried out so that, on the one hand, available results can be incorporated into this project and, on the other hand, cooperation results can be taken into account in ongoing work. Parallel to this, the second project objective is to set up competence groups that, as specialist groups, are familiar with the regional characteristics and help to record the current situation. The first two objectives are supported in particular by workshops and the exchange of researchers. In this way, the partners’ methodology is made accessible to both groups, which significantly promotes the analysis of research topics and the approach. Finally, in the third project objective, practice-oriented and target group-oriented results based on validated case studies will be provided so that the jointly developed methodology can be created. This contribution provides an overview of the activities.
This paper compares two popular scripting implementations for hardware prototyping: Python scripts exe- cut from User-Space and C-based Linux-Driver processes executed from Kernel-Space, which can provide information to researchers when considering one or another in their implementations. Conclusions exhibit that deploying software scripts in the kernel space makes it possible to grant a certain quality of sensor information using a Raspberry Pi without the need for advanced real-time operational systems.
Healthy and good sleep is a prerequisite for a rested mind and body. Both form the basis for physical and mental health. Healthy sleep is hindered by sleep disorders, the medically diagnosed frequency of which increases sharply from the age of 40. This chapter describes the formal specification of an on-course practical implementation for a non-invasive system based on biomedical signal processing to support the diagnosis and treatment of sleep-related diseases. The system aims to continuously monitor vital data during sleep in a patient’s home environment over long periods by using non-invasive technologies. At the center of the development is the MORPHEUS Box (MoBo), which consists of five main conceptualizations: the MoBo core, the MoBo-HW, the MoBo algorithm, the MoBo API, and the MoBo app. These synergistic elements aim to support the diagnosis and treatment of sleep-related diseases. Although there are related developments in individual aspects concerning the system, no comparative approach is known that gives a similar scope of functionality, deployment flexibility, extensibility, or the possibility to use multiple user groups. With the specification provided in this chapter, the MORPHEUS project sets a good platform, data model, and transmission strategies to bring an innovative proposal to measure sleep quality and detect sleep diseases from non-invasive sensors.
Development of an expert system to overpass citizens technological barriers on smart home and living
(2023)
Adopting new technologies can be overwhelming, even for people with experience in the field. For the general public, learning about new implementations, releases, brands, and enhancements can cause them to lose interest. There is a clear need to create point sources and platforms that provide helpful information about the novel and smart technologies, assisting users, technicians, and providers with products and technologies. The purpose of these platforms is twofold, as they can gather and share information on interests common to manufacturers and vendors. This paper presents the ”Finde-Dein-SmartHome” tool. Developed in association with the Smart Home & Living competence center [5] to help users learn about, understand, and purchase available technologies that meet their home automation needs. This tool aims to lower the usability barrier and guide potential customers to clear their doubts about privacy and pricing. Communities can use the information provided by this tool to identify market trends that could eventually lower costs for providers and incentivize access to innovative home technologies and devices supporting long-term care.
The importance of sleep in the life of a human being to function in nowadays society is known from a large number of studies. A standard method for sleep analysis is polysomnography (PSG), which uses multiple sensors to measure and analyze multiple signals, allowing precise and detailed sleep analysis. Nonetheless, the cost of using PSG technologies is high in terms of complexity, personnel and time. To overcome these shortcomings, alternative solutions can be used to reduce costs and increase comfort for patients. The objective of this work is to design and develop a prototype of the software component of the sleep analysis system, taking into account the aspects of data flow, data storage and user interface in addition to data processing. The software components implemented and developed in the Morpheus System and described in this article comprise a usable platform capable of assisting custom research implementations in IoT.
