| Gyrocardiography: A new non-invasive monitoring method for the assessment of cardiac mechanics and the estimation of hemodynamic variables M Jafari Tadi, E Lehtonen, A Saraste, J Tuominen, J Koskinen, M Teräs, ... Scientific reports 7 (1), 6823, 2017 | 169 | 2017 |
| Clinical assessment of a non-invasive wearable MEMS pressure sensor array for monitoring of arterial pulse waveform, heart rate and detection of atrial fibrillation M Kaisti, T Panula, J Leppänen, R Punkkinen, M Jafari Tadi, T Vasankari, ... NPJ digital medicine 2 (1), 39, 2019 | 145 | 2019 |
| A real-time approach for heart rate monitoring using a Hilbert transform in seismocardiograms MJ Tadi, E Lehtonen, T Hurnanen, J Koskinen, J Eriksson, M Pänkäälä, ... Physiological measurement 37 (11), 1885, 2016 | 107 | 2016 |
| Accelerometer‐Based Method for Extracting Respiratory and Cardiac Gating Information for Dual Gating during Nuclear Medicine Imaging M Jafari Tadi, T Koivisto, M Pänkäälä, A Paasio International journal of biomedical imaging 2014 (1), 690124, 2014 | 96 | 2014 |
| Automated detection of atrial fibrillation based on time–frequency analysis of seismocardiograms T Hurnanen, E Lehtonen, MJ Tadi, T Kuusela, T Kiviniemi, A Saraste, ... IEEE journal of biomedical and health informatics 21 (5), 1233-1241, 2016 | 90 | 2016 |
| Seismocardiography: Toward heart rate variability (HRV) estimation MJ Tadi, E Lehtonen, T Koivisto, M Pänkäälä, A Paasio, M Teräs 2015 IEEE International Symposium on Medical Measurements and Applications …, 2015 | 56 | 2015 |
| Multiclass classifier based cardiovascular condition detection using smartphone mechanocardiography Z Iftikhar, O Lahdenoja, M Jafari Tadi, T Hurnanen, T Vasankari, ... Scientific reports 8 (1), 9344, 2018 | 55 | 2018 |
| Gyrocardiography: A new non-invasive approach in the study of mechanical motions of the heart. Concept, method and initial observations MJ Tadi, E Lehtonen, M Pankäälä, A Saraste, T Vasankari, M Terás, ... 2016 38th Annual International Conference of the IEEE engineering in …, 2016 | 51 | 2016 |
| Stand-alone heartbeat detection in multidimensional mechanocardiograms M Kaisti, MJ Tadi, O Lahdenoja, T Hurnanen, A Saraste, M Pänkäälä, ... IEEE Sensors Journal 19 (1), 234-242, 2018 | 48 | 2018 |
| Heart rate variability estimation with joint accelerometer and gyroscope sensing O Lahdenoja, T Humanen, MJ Tadi, M Pänkäälä, T Koivisto 2016 Computing in Cardiology Conference (CinC), 717-720, 2016 | 31 | 2016 |
| A new algorithm for segmentation of cardiac quiescent phases and cardiac time intervals using seismocardiography MJ Tadi, T Koivisto, M Pänkäälä, A Paasio, T Knuutila, M Teräs, ... Sixth International Conference on Graphic and Image Processing (ICGIP 2014 …, 2015 | 30 | 2015 |
| Biomedical image analysis competitions: The state of current participation practice M Eisenmann, A Reinke, V Weru, MD Tizabi, F Isensee, TJ Adler, ... arXiv preprint arXiv:2212.08568, 2022 | 29 | 2022 |
| Classification of atrial fibrillation and acute decompensated heart failure using smartphone Mechanocardiography: a multilabel learning approach S Mehrang, O Lahdenoja, M Kaisti, MJ Tadi, T Hurnanen, A Airola, ... IEEE Sensors Journal 20 (14), 7957-7968, 2020 | 28 | 2020 |
| Comprehensive analysis of cardiogenic vibrations for automated detection of atrial fibrillation using smartphone mechanocardiograms MJ Tadi, S Mehrang, M Kaisti, O Lahdenoja, T Hurnanen, J Jaakkola, ... IEEE Sensors Journal 19 (6), 2230-2242, 2018 | 28 | 2018 |
| A smartphone-only solution for detecting indications of acute myocardial infarction O Lahdenoja, T Koivisto, MJ Tadi, Z Iftikhar, T Hurnanen, T Vasankari, ... 2017 IEEE EMBS International Conference on Biomedical & Health Informatics …, 2017 | 22 | 2017 |
| Adaptive weight aggregation in federated learning for brain tumor segmentation MI Khan, M Jafaritadi, E Alhoniemi, E Kontio, SA Khan International MICCAI Brainlesion Workshop, 455-469, 2021 | 18 | 2021 |
| A miniaturized low power biomedical sensor node for clinical research and long term monitoring of cardiovascular signals J Tuominen, E Lehtonen, MJ Tadi, J Koskinen, M Pänkäälä, T Koivisto 2017 IEEE international symposium on circuits and systems (ISCAS), 1-4, 2017 | 18 | 2017 |
| Machine learning based classification of myocardial infarction conditions using smartphone-derived seismo-and gyrocardiography S Mehrang, MJ Tadi, M Kaisti, O Lahdenoja, T Vasankari, T Kiviniemi, ... 2018 Computing in Cardiology Conference (CinC) 45, 1-4, 2018 | 16 | 2018 |
| Investigating the estimation of cardiac time intervals using gyrocardiography P Dehkordi, K Tavakolian, MJ Tadi, V Zakeri, F Khosrow-Khavar Physiological Measurement 41 (5), 055004, 2020 | 14 | 2020 |
| Deep learning accurately classifies elbow joint effusion in adult and pediatric radiographs JT Huhtanen, M Nyman, D Doncenco, M Hamedian, D Kawalya, ... Scientific Reports 12 (1), 11803, 2022 | 13 | 2022 |
Tero KoivistoProject manager, University of TurkuVerified email at utu.fi
