Keine peer reviewed Publikation (Wissenschaftlicher Artikel und Aufsatz, Proceeding, Artikel in Tagungsband)
Refine
Document Type
- Conference Proceeding (23)
- Article (4)
Has Fulltext
- no (27)
Keywords
- AAL (2)
- Accelerometers (1)
- Activity monitoring (1)
- Ambient assisted living (1)
- Atmung (1)
- BCG (1)
- Ballistocardiography (1)
- Bio-vital data (1)
- Breathing rate (1)
- Convolution (1)
Institute
- Fakultät Informatik (27) (remove)
Sleep quality and in general, behavior in bed can be detected using a sleep state analysis. These results can help a subject to regulate sleep and recognize different sleeping disorders. In this work, a sensor grid for pressure and movement detection supporting sleep phase analysis is proposed. In comparison to the leading standard measuring system, which is Polysomnography (PSG), the system proposed in this project is a non-invasive sleep monitoring device. For continuous analysis or home use, the PSG or wearable Actigraphy devices tends to be uncomfortable. Besides this fact, they are also very expensive. The system represented in this work classifies respiration and body movement with only one type of sensor and also in a non-invasive way. The sensor used is a pressure sensor. This sensor is low cost and can be used for commercial proposes. The system was tested by carrying out an experiment that recorded the sleep process of a subject. These recordings showed the potential for classification of breathing rate and body movements. Although previous researches show the use of pressure sensors in recognizing posture and breathing, they have been mostly used by positioning the sensors between the mattress and bedsheet. This project however, shows an innovative way to position the sensors under the mattress.
This paper presents a bed system able to analyze a person’s movement, breathing and recognize the positions that the subject is lying on the bed during the night without any additional physical contact. The measurements are performed with sensors placed between the mattress and the bed-frame. An Intel Edison board was used as an endpoint that served as a communication node from the mesh network to external service. Two nodes and Intel Edison are attached to the bottom of the bed frame and they are connected to the sensors. First test results have indicated the potential of the proposed approach for the recognition of sleep positions with 83% of correct recognized positions.
The process of restoring our body and brain from fatigue is directly depend-ing on the quality of sleep. It can be determined from the report of the sleep study results. Classification of sleep stages is the first step of this study and this includes the measurement of biovital data and its further processing.
In this work, the sleep analysis system is based on a hardware sensor net, namely a grid of 24 pressure sensors, supporting sleep phase recognition. In comparison to the leading standard, which is polysomnography, the proposed approach is a non-invasive system. It recognises respiration and body move-ment with only one type of low-cost pressure sensors forming a mesh archi-tecture. The nodes implement as a series of pressure sensors connected to a low-power and performant microcontroller. All nodes are connected via a system wide bus with address arbitration. The embedded processor is the mesh network endpoint that enables network configuration, storing and pre-processing of the data, external data access and visualization.
The system was tested by executing experiments recording the sleep of different healthy young subjects. The results obtained have indicated the po-tential to detect breathing rate and body movement. A major difference of this system in comparison to other approaches is the innovative way to place the sensors under the mattress. This characteristic facilitates the continuous using of the system without any influence on the common sleep process.
We identify 74 generic, reusable technical requirements based on the GDPR that can be applied to software products which process personal data. The requirements can be traced to corresponding articles and recitals of the GDPR and fulfill the key principles of lawfulness and transparency. Therefore, we present an approach to requirements engineering with regard to developing legally compliant software that satisfies the principles of privacy by design, privacy by default as well as security by design.
To get a better understanding of Cross Site Scripting vulnerabilities, we investigated 50 randomly selected CVE reports which are related to open source projects. The vulnerable and patched source code was manually reviewed to find out what kind of source code patterns were used. Source code pattern categories were found for sources, concatenations, sinks, html context and fixes. Our resulting categories are compared to categories from CWE. A source code sample which might have led developers to believe that the data was already sanitized is described in detail. For the different html context categories, the necessary Cross Site Scripting prevention mechanisms are described.
We investigated 50 randomly selected buffer overflow vulnerabilities in Firefox. The source code of these vulnerabilities and the corresponding patches were manually reviewed and patterns were identified. Our main contribution are taxonomies of errors, sinks and fixes seen from a developer's point of view. The results are compared to the CWE taxonomy with an emphasis on vulnerability details. Additionally, some ideas are presented on how the taxonomy could be used to improve the software security education.