Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Mirco Fuchs"'
Publikováno v:
Sensors, Vol 21, Iss 18, p 6022 (2021)
Exploiting photoplethysmography signals (PPG) for non-invasive blood pressure (BP) measurement is interesting for various reasons. First, PPG can easily be measured using fingerclip sensors. Second, camera based approaches allow to derive remote PPG
Externí odkaz:
https://doaj.org/article/4940d900a6d147a284d675dc2bfdc04a
Publikováno v:
Current Directions in Biomedical Engineering. 8:423-426
Pain assessment in clinical settings can be a challenging task for clinic staff and patients. An automatic and contactless pain estimation system via facial expression is a decisive advantage. In the following article we present a method for pain cla
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1511335352f474377a68b0cb68d7a66
https://doi.org/10.1515/cdbme-2022-1108
https://doi.org/10.1515/cdbme-2022-1108
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 29:54-67
In this study we compared various neural network types for the task of automatic infant vocalization classification, i.e convolutional, recurrent and fully-connected networks as well as combinations of thereof. The goal was to first determine the opt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0a0aa0881a708b1c189cb93b9db5b211
https://doi.org/10.1109/taslp.2020.3037414
https://doi.org/10.1109/taslp.2020.3037414
Publikováno v:
Speech Communication. 119:36-45
In this study we investigated Convolutional Neural Networks (CNNs) for the classification of infant vocalization sequences. The target classes were ‘crying’, ‘fussing’, ‘babbling’, ‘laughing’ and ‘vegetative vocalizations’. The ge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5b463aded8208811a3e52fbea503638
https://doi.org/10.1016/j.specom.2020.03.003
https://doi.org/10.1016/j.specom.2020.03.003
Photoplethysmographic (PPG) signals offer diagnostic potential beyond heart rate analysis or blood oxygen level monitoring. In the recent past, research focused extensively on non-invasive PPG-based approaches to blood pressure (BP) estimation. These
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b251856755f2e5a2abee6f09f6c9dc3
Publikováno v:
CVPR Workshops
Exploiting photoplethysmography signals (PPG) for non-invasive blood pressure (BP) measurement is interesting for various reasons. First, PPG can easily be measured using fingerclip sensors. Second, camera-based approaches allow to derive remote PPG
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::48f048d81e983ccbe3eb3fe8f6d37486
https://doi.org/10.1109/cvprw53098.2021.00423
https://doi.org/10.1109/cvprw53098.2021.00423
Publikováno v:
Ecological Informatics. 65:101423
Automatic detection systems are important in passive acoustic monitoring (PAM) systems, as these record large amounts of audio data which are infeasible for humans to evaluate manually. In this paper we evaluated methods for compensating class imbala
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5edf1492dc6283e7d39f65d6509d0538
https://doi.org/10.1016/j.ecoinf.2021.101423
https://doi.org/10.1016/j.ecoinf.2021.101423
Publikováno v:
Sensors, Vol 21, Iss 6022, p 6022 (2021)
Sensors
Volume 21
Issue 18
Sensors (Basel, Switzerland)
Sensors
Volume 21
Issue 18
Sensors (Basel, Switzerland)
Exploiting photoplethysmography signals (PPG) for non-invasive blood pressure (BP) measurement is interesting for various reasons. First, PPG can easily be measured using fingerclip sensors. Second, camera based approaches allow to derive remote PPG
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::476f8cd628e1d228d2b8cd2a2e203b03
https://doi.org/10.3390/s21186022
https://doi.org/10.3390/s21186022
Publikováno v:
CVPR Workshops
Determining a waterline in images recorded in canoe sprint training is an important component for the kinematic parameter analysis to assess an athlete's performance. Here, we propose an approach for the automated waterline detection. First, we utili
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ae1398d7b230a9b847ec95a208929fe
Publikováno v:
EMBC
In recent years, considerable progress has been made in the non-contact based detection of the respiration rate from video sequences. Common techniques either directly assess the movement of the chest due to breathing or are based on analyzing subtle
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b6066200de4f2807994519dac7e33b8a
https://doi.org/10.1109/embc.2019.8856387
https://doi.org/10.1109/embc.2019.8856387