TY - GEN
T1 - CovidSense
T2 - 9th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-Exclusion, DSAI 2020
AU - Tsoumalis, Georgios
AU - Bampos, Zafeirios
AU - Papazoglou, Athanasios
AU - Iakovakis, Dimitrios
AU - Hadjidimitriou, Stelios
AU - Apostolidis, Georgios
AU - Charisis, Vasileios
AU - Jelinek, Herbert
AU - Khandoker, Ahsan
AU - Khalaf, Kinda
AU - Damiani, Ernesto
AU - Hadjileontiadis, Leontios
N1 - Funding Information:
Considering the impact of the worldwide COVID-19 outbreak (more than 55.200.000 incidences and more than 1.330.000 deaths so far1, along with a third of the global population having experienced coronavirus lockdown from March up to June 2020), it is clear that there is an immediate need to devise an effective tool that can be used both at the hospital and home sites to provide a reliable risk index of confronting COVID-19. In this vein, some very recent, yet limited, attempts have been proposed to create Web and smartphone apps, that could assist in the creation of feedback to the user for possible COVID-19 infection risk. The latter include the Apple COVID-19 screening tool (https://www.apple.com/covid19/., released March 27, 2020, in collaboration with the Centers for Disease Control and Prevention (CDC), Federal Emergency Management Agency (FEMA), and the White House. Nevertheless, this screening tool only takes into account the user’s response to a questionnaire, without any validation based on his/her physiological signals. More recently (April 1, 2020), Cambridge University, UK, announced the project COVID-19 Sounds App (https://www.COVID-19-sounds.org/en/., funded by the European Research Council with € 2.5million, to develop an App that could record breathing and coughing sounds to infer for the risk of COVID-19 infection. Although COVID-19 Sounds closes the feedback loop from the user’s questionnaires respond via the analysis of his/her bioacoustics signals, it does not record any HRV signals, clearly missing out the direct link of the ANS with the immune system status.
Funding Information:
This work is financially supported by the Khalifa University of Science and Technology: COVID-19 and Future Pandemic Programme with Grant No: CPRA 8474000314.
Publisher Copyright:
© 2020 ACM.
PY - 2020/12/2
Y1 - 2020/12/2
N2 - Coronavirus Disease COVID-19 is a new strain of coronavirus, first identified in clusters with pneumonia-like symptoms with manifestation mainly of fever (>37.8oC), runny nose, dry cough, anosmia, loss of taste, and fatigue. Testing for COVID-19 can be carried out on samples obtained by various methods, including nasopharyngeal swab or sputum sample. Results are generally available within a few hours to one day. Taking into consideration the worldwide COVID-19 pandemic impact (more than 35.500.000 incidences and more than 1.000.000 deaths so far), it is clear that there is an immediate need to devise an effective tool that can be used both at the hospital and home sites to provide a reliable risk index of confronting COVID-19. Here, the potentialities of a smartphone-based app, namely CovidSense, that could provide a reliable COVID-19 risk index to the user before performing any relevant clinical test, monitor his/her symptoms and provide guidance for further actions are presented. CovidSense is a holistic approach for COVID-19 risk assessment that captures both the status of the respiratory system, via acquisition and AI-based analysis of breathing and coughing sounds, along with the Autonomic Nervus System/Immune System status, via the capturing and analysis of the Heart Rate Variability. The analytical description and functionality of the CovidSense included here manifests the usefulness of such approach in continuous symptoms monitoring, allowing people with early symptoms, quarantined and sensitive groups, such as older adults and patients with comorbidities, to become active participants in the effort of fighting the spread of COVID-19, by monitoring their status and get engaged in appropriate preventative actions. CovidSense paves the way for solutions using technological artifacts, such as smartphones, to foster inclusiveness and joint efforts in successfully addressing global health problems, such as the COVID-19 pandemic.
AB - Coronavirus Disease COVID-19 is a new strain of coronavirus, first identified in clusters with pneumonia-like symptoms with manifestation mainly of fever (>37.8oC), runny nose, dry cough, anosmia, loss of taste, and fatigue. Testing for COVID-19 can be carried out on samples obtained by various methods, including nasopharyngeal swab or sputum sample. Results are generally available within a few hours to one day. Taking into consideration the worldwide COVID-19 pandemic impact (more than 35.500.000 incidences and more than 1.000.000 deaths so far), it is clear that there is an immediate need to devise an effective tool that can be used both at the hospital and home sites to provide a reliable risk index of confronting COVID-19. Here, the potentialities of a smartphone-based app, namely CovidSense, that could provide a reliable COVID-19 risk index to the user before performing any relevant clinical test, monitor his/her symptoms and provide guidance for further actions are presented. CovidSense is a holistic approach for COVID-19 risk assessment that captures both the status of the respiratory system, via acquisition and AI-based analysis of breathing and coughing sounds, along with the Autonomic Nervus System/Immune System status, via the capturing and analysis of the Heart Rate Variability. The analytical description and functionality of the CovidSense included here manifests the usefulness of such approach in continuous symptoms monitoring, allowing people with early symptoms, quarantined and sensitive groups, such as older adults and patients with comorbidities, to become active participants in the effort of fighting the spread of COVID-19, by monitoring their status and get engaged in appropriate preventative actions. CovidSense paves the way for solutions using technological artifacts, such as smartphones, to foster inclusiveness and joint efforts in successfully addressing global health problems, such as the COVID-19 pandemic.
KW - AI
KW - Autonomic Nervus System/immune System status
KW - Breathing sounds
KW - Coughing Sounds
KW - COVID-19 pandemic
KW - CovidSense app
KW - Heart Rate Variability
UR - http://www.scopus.com/inward/record.url?scp=85108081218&partnerID=8YFLogxK
U2 - 10.1145/3439231.3439275
DO - 10.1145/3439231.3439275
M3 - Conference contribution
AN - SCOPUS:85108081218
T3 - ACM International Conference Proceeding Series
SP - 87
EP - 92
BT - 9th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-Exclusion, DSAI 2020
Y2 - 2 December 2020 through 4 December 2020
ER -
