Design of e-Health System for Heart Rate and Lung Sound Monitoring with AI-based Analysis

Author(s):  
Kuei-Chung Chang ◽  
Jun-Wei Huang ◽  
Yi-Fong Wu
BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e041071
Author(s):  
Hanna Oommen ◽  
Kunal Ranjan ◽  
Sudha Murugesan ◽  
Aboli Gore ◽  
Sunil Sonthalia ◽  
...  

ObjectivesGlobally, half of all stillbirths occur during birth. Detection of fetal distress with fetal heart rate monitoring (FHRM), followed by appropriate and timely management, might reduce fresh stillbirths and neonatal morbidity. This study aimed to investigate the barriers and facilitators for the implementation of Moyo FHRM use in Bihar state, and secondarily, the feasibility of collecting reliable obstetrical and neonatal outcome data to assess the effect of implementation.SettingCARE Bihar and the hospital management at four district hospitals (DHs) in Bihar state, each with 6500 to 15 000 deliveries a year, agreed to testing the implementation of Moyo FHRM through a process of meetings, training sessions and collecting data. At each hospital, a clinical training expert was trained to train others, while a clinical assessment facilitator collected data.MethodologyObservational notes were taken at all training sessions and meetings. Individual interviews (n=4) were conducted with clinical training experts (CTEs) on training experiences and barriers and facilitators for Moyo FHRM implementation. The CTEs recoded field notes in diaries. Descriptive analyses performed on pre-implementation and post-implementation data (n=521) assessed quality and completeness.ResultsMain barriers to implementation of Moyo FHRM were health system and cultural challenges involving (1) existing practices, (2) insufficient human resources, (3) action delays and (4) cultural and local challenges. Another barrier was insufficient involvement of doctors. Facilitators for implementation were easy use of the Moyo FHRM device and adequate training for staff.Electronic collection of obstetrical data worked well but had substantial missing data.ConclusionHealth system and cultural challenges are a major constraint to Moyo FHRM implementation in low-resource settings. Improvements at all levels of infrastructure, practices and skills will be critical in busy DHs in Bihar. Full-scale implementation needs doctor-led leadership and ownership. Obstetrical data collection for the purpose of scientific analysis needs to be improved.


2019 ◽  
Author(s):  
Volker Gross ◽  
Patrick Fischer ◽  
Andreas Weissflog ◽  
Olaf Hildebrandt ◽  
Ulrich Koehler ◽  
...  

Abstract Background Cough is an important respiratory symptom being of great interest to many researchers. Up to now, most knowledge about cough has been collected through standardized questionnaires. Objective, and reliable detection of cough assessed by automated lung sound monitoring are becoming increasingly important. The aim of this study is to validate the LEOSound lung sound monitor by using previously determined and investigated COPD datasets (1,2). Methods Based on multiple recordings of 48 patients with stable COPD II-IV, we validated the cough detection algorithm of LEOSound by using a contingency table. Sensitivity, specificity, positive and negative predictive values were used as quantitative measures. Results We found the overall accuracy to be 87.3% with sensitivity and specificity of 98.7% and 80.2%, respectively. Major reasons for midsections in descending order were throat cleaning, snoring and movement artifacts. Conclusion In comparison to other full-automated cough monitoring systems, the LEOSound performs the best in sensitivity, but shows slightly poor specificity. Misdetections were mainly caused due to morphological similar noises and can be withdrawn while scanning through the recording manually.


2009 ◽  
Vol 47 (09) ◽  
Author(s):  
S Kunsch ◽  
TM Gress ◽  
V Ellenrieder ◽  
V Gross ◽  
U Köhler

Thorax ◽  
1995 ◽  
Vol 50 (9) ◽  
pp. 955-961 ◽  
Author(s):  
A B Bohadana ◽  
R Peslin ◽  
H Uffholtz ◽  
G Pauli

Pneumologie ◽  
2016 ◽  
Vol 70 (S 01) ◽  
Author(s):  
U Koehler ◽  
A Weissflog ◽  
W Nikolaizik ◽  
O Hildebrandt ◽  
M Scholtes ◽  
...  

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