The objectives of this study are to evaluate the impact of the CoVID-19 pandemic on the development of relevant emerging digital healthcare trends and to explore which digital healthcare trend does the health industry need most to support HCPs. A web survey using 39 questions facilitating Five-Point Likert scales was performed from 1.8.2020 – 31.10.2020. Of 260 participants invited, 90 participants answered the questionnaire. The participants were located in the Hospital/HCP sector in 11.9%, in other healthcare sectors in 22.2%, in the pharmaceutical sector in 11.1%, in the medical device and equipment industry in 43.3%. The Five-Point Likert scales were in all cases fashioned as from 1 (strongly disagree) to 5 (strongly agree). As the top 3 most impacted digital health care trends strongly impacted by CoVID-19, respondents named:. - remote management of patients by telemedicine, mean answer 4.44. - shared data governance under patient control, mean answer 3.80. - new virtual interaction between HCP´s and medical industry, mean answer 3.76. Respondents were asked which level of readiness of the healthcare system currently possess to cope with the current trend impacted by CoVID-19. - Digital and efficient healthcare logistics, mean answer 1.54. - Integrated health care, mean answer 1.73. - Use of big data and artificial intelligence, mean answer 2.03. Asked if collaborative research in the form of digital data platforms for research data sharing and increasing collaboration with multi-centric consortia would have a positive impact on the healthcare sector, the agreement was high with a value of mean 4.10 on the scale. We can conclude that the impact of COVID-19 appears to be a high agreement of necessary advances in digitalization in the health care sector and in the collaboration of HCPs with the health care industry. Health care professional are unsure, in how far the national health care sector is capable of transformation in healthcare logistics and integrated health care

The tendency towards using inertial sensors for remote monitoring of the patients at home is increasing. One of the most important characteristics of the sensors is sampling rate. Higher sampling rate results in higher resolution of the sampled signal and lower amount of noise. However, higher sampling frequency comes with a cost. The main aim of our study was to determine the validity of measurements performed by low sampling frequency (12.5 Hz) accelerometers (SENS) in patients with knee osteoarthritis compared to standard sensor-based motion capture system (Xsens). We also determined the test-retest reliability of SENS accelerometers. Participants were patients with unilateral knee osteoarthritis. Gait analysis was performed simultaneously by using Xsens and SENS sensors during two repetitions of over-ground walking at a self-selected speed. Gait data from Xsens were used as an input for AnyBody musculoskeletal modeling software to measure the accelerations at the exact location of two defined virtual sensors in the model (VirtualSENS). After preprocessing, the signals from SENS and VirtualSENS were compared in different coordinate axes in time and frequency domains. ICC for SENS data from first and second trials were calculated to assess the repeatability of the measurements. We included 32 patients (18 females) with median age 70.1[48.1 – 85.4]. Mean height and weight of the patients were 173.2 ± 9.6 cm and 84.2 ± 14.7 kg respectively. The correlation between accelerations in time domain measured by SENS and VirtualSENS in different axes was r = 0.94 in y-axis (anteroposterior), r = 0.91 in x-axis (vertical), r = 0.83 in z-axis (mediolateral), and r = 0.89 for the magnitude vector. In frequency domain, the value and the power of fundamental frequencies (F. 0. ) of SENS and VirtualSENS signals demonstrated strong correlation (r = 0.98 and r = 0.99 respectively). The result of test-retest evaluation showed excellent repeatability for acceleration measurement by SENS sensors. ICC was between 0.89 to 0.94 for different coordinate axes. Low sampling frequency accelerometers can provide valid and reliable measurements especially for home monitoring of the patients, in which handling big data and sensors cost and battery lifetime are among important issues