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    traqbeat

Traqbeat Technologies PC is a fast-growing company with acknowledged excellence in conducting high-level research and development of innovative systems and services. Its activities focus on the development of a novel adaptable wearable health tracking device including quantitative health risk assessment methods and tools focusing on the wider area of medical sensing and informatics, e-health, m-Health, and Internet of Medical Things. Its goal is to develop and apply its novel technology in the wider context of personalized, predictive and preventive medicine aiming at the optimal management of diseases and the development of clinical decision support systems, optimization of diagnosis and disease combating tools and models for enhancing biomedical knowledge discovery.

The company realizes its goals through strong interaction between interdisciplinary engineers, product and operating managers with high R&D experience. Traqbeat’s expertise is on modern ICT, smart biomedical sensors, mobile and wireless technology platforms and service-oriented infrastructures for specialized embedded systems and ubiquitous monitoring applications. Traqbeat’s founders have long experience in implementing national and European projects, high level technological competence and thorough knowledge and understanding of the field. They have participated and coordinated European, National and Commercial R&D projects related to Medical Informatics, Biomedical Informatics and Engineering. Traqbeat’s core technology consist of a proprietary – in house – developed novel battery-powered, wearable sensor and methods (patent pending) capable of continuously or intermittently measuring and recording of multiple health related biomarkers such as Heart Rate (HR), Heart Rate Variability (HRV), Blood Oxygen Levels (SpO2), Respiration Rate (RR), Blood Pressure (BP), Temperature and Electrocardiograph (ECG), on a need be basis. This enabling technology consists of precisely designed electronics and optical hardware for optimal signal capture, as well as state-of-the-art signal analysis and machine learning methods.

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