TY - CHAP A1 - Gaiduk, Maksym A1 - Vunderl, Bruno A1 - Seepold, Ralf A1 - Ortega, Juan Antonio A1 - Penzel, Thomas T1 - Sensor-Mesh-Based System with Application on Sleep Study T2 - Bioinformatics and Biomedical Engineering, 6th International Work-Conference (IWBBIO 2018), 25th-27th April 2018, Granada, Spain - (Lecture Notes in Computer Science ; Vol. 10814) N2 - 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. KW - Movement detection KW - Respiration rate KW - Sleep study KW - FSR sensor Y1 - 2018 SN - 978-3-319-78759-6 SN - 978-3-319-78758-9 U6 - http://dx.doi.org/10.1007/978-3-319-78759-6_34 SP - 371 EP - 382 PB - Springer CY - Cham ER - TY - CHAP A1 - Gaiduk, Maksym A1 - Kuhn, Ina A1 - Seepold, Ralf A1 - Ortega, Juan Antonio A1 - Martínez Madrid, Natividad T1 - A sensor grid for pressure and movement detection supporting sleep phase analysis T2 - Bioinformatics and Biomedical Engineering, 5th International Work-Conference (IWBBIO 2017), Granada, Spain, April 26–28, 2017, Proceedings, Part II, (Lecture Notes in Computer Science ; 10209) N2 - 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. KW - Sensor grid KW - Movement detection KW - Sleep phase KW - Force resistor sensor Y1 - 2017 SN - 978-3-319-56154-7 SN - 978-3-319-56153-0 U6 - http://dx.doi.org/10.1007/978-3-319-56154-7_53 SP - 596 EP - 607 PB - Springer CY - Cham ER -