Periodic Reporting for period 2 - WECARMON (Wearable Cardiorespiratory Monitor)
Periodo di rendicontazione: 2019-10-09 al 2020-10-08
The WECARMON’s main objective is to develop a novel system for monitoring patients suffering of cardiorespiratory diseases. It is based on a very comfortable wearable armband which can monitor some cardiorespiratory parameters during the patients’ normal life. Its innovative nature is based on two main tools: 1) a long-term (months) wearable ECG device which uses dry electrodes which causes no skin irritation and which are placed in a leadless armband, and 2) signal processing techniques for estimating respiratory rate and volumes from ECG which are robust against artefacts generated by movements during daily life.
Among the wide range of applications that a long-term cardiorespiratory monitor has (including monitoring of sleep, stress level, fitness level, and chronic respiratory patients), WECARMON is focused on the monitoring of chronic respiratory patients.
An (OSAS) screening based on such a comfortable and wearable device would be an excellent alternative to the polysomnography (quite involved and difficult to use in ambulatory scenario), being more comfortable for the patient and economic for the society. Furthermore, depending on the results obtained when evaluating the armband device for OSAS screening, we could think of monitoring the patient during some weeks in order to assess the effectiveness of the treatment and to adapt it in case it is needed. Other patients whose monitoring is interesting are COPD and/or asthma patients. These patients are affected by destabilizations (or “exacerbations”) which makes them to seek medical help and often lead to their hospitalization. Exacerbations can start quickly (in minutes to hours) and they are one of the main causes of mortality among patients with COPD and asthma which are the two most common chronic respiratory diseases, affecting millions of children and adults. The wearable armband may allow us to early detect COPD/asthma exacerbations and lead to a better prognosis of the patient and a reduction of financial costs to society.
The wearable armband provided good quality ECG data during more than a half of the non-bedtime, and during almost all the bedtime, and respiratory rate was successfully estimated from the armband-ECG signals by using a ECG-derived-respiration (EDR) methods. In addition, the amplitudes of these EDR signals showed a correlation with the tidal volume higher than 0.9 (inter-subject median), suggesting that the armband can track not only respiratory rate, but also changes in tidal volume. These results are promising and allow us to consider the armband ECG device as a potential wearable cardiorespiratory monitor.
The coronavirus disease pandemic made the contact-requiring experiments not recommendable, specially for respiratory patients. WECARMON project was redirected to early detection of SARS-COV-2 infection based on same physiological information that was planned to be used for patients monitoring. A new objective was set: the development of a smartphone application for obtaining this physiological information by using a pulse photoplethysmographic (PPG) signal recorded by the camera and flashlight. An Android application that records that PPG and stores it in “the cloud” (once anonymized) was created, and a visual inspection revealed that the signals have enough quality to obtain the desired physiological information. The application is currently being validated.
Among the wide range of applications that a long-term cardiorespiratory monitor has (including monitoring of sleep, stress level, fitness level, and chronic respiratory patients), WECARMON is focused on the monitoring of chronic respiratory patients.
An (OSAS) screening based on such a comfortable and wearable device would be an excellent alternative to the polysomnography (quite involved and difficult to use in ambulatory scenario), being more comfortable for the patient and economic for the society. Furthermore, depending on the results obtained when evaluating the armband device for OSAS screening, we could think of monitoring the patient during some weeks in order to assess the effectiveness of the treatment and to adapt it in case it is needed. Other patients whose monitoring is interesting are COPD and/or asthma patients. These patients are affected by destabilizations (or “exacerbations”) which makes them to seek medical help and often lead to their hospitalization. Exacerbations can start quickly (in minutes to hours) and they are one of the main causes of mortality among patients with COPD and asthma which are the two most common chronic respiratory diseases, affecting millions of children and adults. The wearable armband may allow us to early detect COPD/asthma exacerbations and lead to a better prognosis of the patient and a reduction of financial costs to society.
The wearable armband provided good quality ECG data during more than a half of the non-bedtime, and during almost all the bedtime, and respiratory rate was successfully estimated from the armband-ECG signals by using a ECG-derived-respiration (EDR) methods. In addition, the amplitudes of these EDR signals showed a correlation with the tidal volume higher than 0.9 (inter-subject median), suggesting that the armband can track not only respiratory rate, but also changes in tidal volume. These results are promising and allow us to consider the armband ECG device as a potential wearable cardiorespiratory monitor.
The coronavirus disease pandemic made the contact-requiring experiments not recommendable, specially for respiratory patients. WECARMON project was redirected to early detection of SARS-COV-2 infection based on same physiological information that was planned to be used for patients monitoring. A new objective was set: the development of a smartphone application for obtaining this physiological information by using a pulse photoplethysmographic (PPG) signal recorded by the camera and flashlight. An Android application that records that PPG and stores it in “the cloud” (once anonymized) was created, and a visual inspection revealed that the signals have enough quality to obtain the desired physiological information. The application is currently being validated.
Different strategies for improving the quality of the ECG signal recorded by the armband were investigated, and different morphological features were studied for artifact detection. An artifact detector based on machine learning was developed. 24-hours recordings were analyzed, and obtained results suggest that the armband device is suitable for a daily life monitoring, obtaining usable data during more than half of the non-bedtime and almost all the bedtime. Five traditional heart rate variability (HRV) were also analyzed. The obtained Pearson’s correlation coefficient between the measurements from the armband device and the measures from a commercial Holter were higher than 0.99 suggesting that the quality of armband-ECG signals is enough to estimate HRV parameters during stationary movement restricted conditions.
A study on deriving respiratory rate using the wearable armband was performed. The study included paced breathing stages at 10, 12, 18, 24, and 30 breaths per minute, as well as an stage during spontaneous breathing. Respiratory rate was estimated from the armband-ECG signals, and the estimates were compared to those obtained from the respiration signal. The obtained relative error that was not higher than 1.25% in median and not higher than 2.78% for all the studied stages. In addition, the methods were modified in order to reduce their computational time. The adaptation reduced the computational time up to a 82.05% assuming a lower accuracy, specifically, the highest median of relative error increased to -1.33%, and its highest IQR increased to 4.22%. Moreover, an algorithm for tracking tidal volume by using the ECG was developed. In this case, the amplitude of the EDR signals was studied as a surrogate of tidal volume. Obtained correlations between EDR amplitude and tidal volume were higher than 0.9 for some EDR methods, suggesting that it is feasible to track tidal volume changes with the armband. These results are very promising and allow us to consider the armband wearable device as a potential wearable cardiorespiratory monitor.
Alternatively, PPG signals were analyzed also, as this technology is the basis of many wearable devices in the market. Novel methods for deriving respiratory rate from PPG signals were proposed focused on noisy environments. Furthermore, methods for estimating baroreflex sensitivity from PPG signal were developed, leading to another source of information about autonomic nervous system.
An Android application that records that PPG and stores it in “the cloud” (once anonymized) was created. Simultaneous smartphone-PPG recordings and conventional PPG recordings are being performed in order to validate the Android application.
WECARMON’s results were disseminated within 13 international conference proceedings and 16 scientific journal articles, that can be found on the ‘Results’ tab.
A study on deriving respiratory rate using the wearable armband was performed. The study included paced breathing stages at 10, 12, 18, 24, and 30 breaths per minute, as well as an stage during spontaneous breathing. Respiratory rate was estimated from the armband-ECG signals, and the estimates were compared to those obtained from the respiration signal. The obtained relative error that was not higher than 1.25% in median and not higher than 2.78% for all the studied stages. In addition, the methods were modified in order to reduce their computational time. The adaptation reduced the computational time up to a 82.05% assuming a lower accuracy, specifically, the highest median of relative error increased to -1.33%, and its highest IQR increased to 4.22%. Moreover, an algorithm for tracking tidal volume by using the ECG was developed. In this case, the amplitude of the EDR signals was studied as a surrogate of tidal volume. Obtained correlations between EDR amplitude and tidal volume were higher than 0.9 for some EDR methods, suggesting that it is feasible to track tidal volume changes with the armband. These results are very promising and allow us to consider the armband wearable device as a potential wearable cardiorespiratory monitor.
Alternatively, PPG signals were analyzed also, as this technology is the basis of many wearable devices in the market. Novel methods for deriving respiratory rate from PPG signals were proposed focused on noisy environments. Furthermore, methods for estimating baroreflex sensitivity from PPG signal were developed, leading to another source of information about autonomic nervous system.
An Android application that records that PPG and stores it in “the cloud” (once anonymized) was created. Simultaneous smartphone-PPG recordings and conventional PPG recordings are being performed in order to validate the Android application.
WECARMON’s results were disseminated within 13 international conference proceedings and 16 scientific journal articles, that can be found on the ‘Results’ tab.
WECARMON project has led to a long-term (months) wearable device that can provide cardiorespiratory information (including heart rate,respiratory rate, and tidal volume estimation), and.autonomic nervous system information. This has a big interest and possibilities for ambulatory environments (even without the tidal volume estimation) with its both economic and social advantages, especially in cases for which the conventional respiration monitors (plethysmographs, pneumographs, spirometers…) are not convenient such as OSAS, COPD, and epilepsy, among others. In addition, it allows a daily-basis monitoring of the patient providing a lot of data which can be used to adapt the treatment, so the wearable monitoring can be used for personalized medicine.
Furthermore, the respiratory and other autonomic-nervous-system markers developed during the WECARMON project have been explored in other clinical applications, including sleep apnea for stratification of cardiovascular risk, stress level assessment, and prediction of predictor of patients’ readiness for weaning from mechanical ventilation.
Furthermore, the respiratory and other autonomic-nervous-system markers developed during the WECARMON project have been explored in other clinical applications, including sleep apnea for stratification of cardiovascular risk, stress level assessment, and prediction of predictor of patients’ readiness for weaning from mechanical ventilation.