The paper presents the implementation and use of the IT system implemented in the Department of Pulmonology of The University Hospital in Cracow. The system integrates data from heterogeneous sources of therapy, diagnosis and medical test results of patients with Obstructive Sleep Apnea (OSA). The article presents the main architectural assumptions of the system, as well as an example of data mining analyzes based on the data served by the system. The example of the research aims to present the possibilities offered by the integration of clinical data in telemedicine and the diagnosis of patients with sleep disordered breathing that may lead to certain comorbidities and premature death.
Sensors that perform the task of measuring the physical quantity of acceleration are discussed. Applications for such measurements and thus of accelerometers, range from early diagnosis procedures for tremor-related diseases (e.g. Parkinsons) to monitoring daily patterns of patient activity using telemetry systems. The system-level requirements in such applications are considered and two novel neural network transducer designs developed by the authors are presented which aim to satisfy such requirements. Both designs are based on a micromachined sensing element with capacitive signal pick-off. The first is an open-loop design utilising a direct inverse control strategy, whilst the second is a closed-loop design where electrostatic actuation is used as a form of feedback. Both transducers are nonlinearly compensated, capable of self-test and provide digital outputs.
A portable laser emission spectro-analyser for analysis of chemical constitution of materials is described in the paper and examples of its applications are given.
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