About Us

The SATHeart concept is born in 2008 and has always been centred around the cardiovascular and respiratory systems, and blood pulse wave analysis. The founder of SATHeart have long experiences in the fields of biomedical engineering, biosignal processing, electronics, life science and integrative medicine.

We extracts parameters from biosignals and in particular the blood pulse wave to provide users, physicians and clinicians with cardiac function parameters, especially linked with cardiac and mental stress.

We also provide users with solutions to re-balance the autonomic nervous system and improve the cardiac function.

Herbert Schwabl, Ph.D

Patrick Celka, Ph.D

Katariina Granqvist, MSc
Herbert graduated in physics, specialized in biophysics and foundations of quantum mechanics. Medicine is the other scientific aspect, especially Tibetan (Eastern) medicine. Herbert is CEO of PADMA.
Patrick has been working in academic and industry for 30 years in the field of digital medical device and algorithm design and implementation. Patrick is developing algorithms for SATHeart.

  • SAT stands for Sensory Active Technology,
  • SAT is also the acronym of our three energetic principles: Stability, Activity and Transformation,
  • SAT is also a Sanskrit term which can tentatively be translated as ultimate, essence, or harmony.

Relevant Patents from our team

  • US 7018338, Method and device for pulse rate detection, granted 2006
  • US 7175601, Portable equipment for measuring and/or monitoring the heart rate, granted 2007
  • EP 1.297.784, Method and device for pulse rate detection, granted 2010
  • PCT/AU2013/000564, Method and Apparatus for Predicting Cardio-Pulmonary Events, Filed 2013
  • PCT/AU2013AOOOS64. Method and apparatus for monitoring cardio-pulmonary health, granted 2015
  • PCT/EP2013/064678, A method and system for determining the state of a person, granted 2014
  • WO 2017/212120 Al, Multi-Sensor System for Estimating Blood Pulse Wave Characteristics, granted 2017
  • EP 181728429, Floating Cardiac Activity Sensor for Sports Equipment Handle, granted 2019
  • EP 19178174.9, System for measuring stress level, Filed June 2019

Relevant Publications

  • Celka, P, Samten, L, Brucet, M and Alabdulgader, A. (2020). Pulse Wave Harmony: Ancient Wisdoms for Modern Age, to be submitted, International Journal of Environmental Research and Public Health, Special Issue “Health and Energetic Environment”
  • Celka, P, Charlton, P. H., Farukh, B., Chowienczyk, P., & Alastruey, J. (2019). Influence of mental stress on the pulse wave features of photoplethysmograms. Under review, Healthcare Technology Letters
  • Celka, P., Granqvist, N., Schwabl, H., & Edwards, S. D. (2019). Development and evaluation of a cardiac coherence index for sleep analysis. Journal of Psychology in Africa, (Special section on HeartMath for Psychology), accepted for publication
  • Charlton, P. H., Celka, P., Farukh, B., Chowienczyk, P., & Alastruey, J. (2018). Assessing mental stress from the photoplethysmogram: A numerical study. Physiological Measurement, 39(5), 054001.
  • Celka, P., Martinmaki, K., Korhonen, T., Santaniemi, N., & Virkkala, J. (2018). Sleep-wake detection and computation of sleep continuity from a wrist unit in children, adolescents and adults. In IFMBE Proceedings (Vol. 65).
  • Delgado-Gonzalo, R., Celka, P., Renevey, P., Dasen, S., Sola, J., Bertschi, M., & Lemay, M. (2015). Physical activity profiling: Activity-specific step counting and energy expenditure models using 3D wrist acceleration. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (Vol. 2015-Novem)
  • Bertschi, M., Celka, P., Delgado-Gonzalo, R., Lemay, M., Calvo, E. M., Grossenbacher, O., & Renevey, P. (2015). Accurate walking and running speed estimation using wrist inertial data. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 8083–8086).
  • Renevey, P., Celka, P., Arberet, S., Calvo, E. M., Carós, J. S. i, Sartori, C., Lemay, M. (2014). Photoplethysmography-based Bracelet for Automatic Sleep Stages Classification: Preliminary Results. In Biomedical Engineering / 817: Robotics Applications. Calgary,AB,Canada: ACTAPRESS.
  • Celka, P., & Kilner, B. (2006). Carmeli’s S index assesses motion and muscle artefact reduction in rowers’ electrocardiograms. Physiological Measurement, 27(8), 737.
  • Celka, P., & Patrick. (2005). Neuronal coordination in the brain: A signal processing perspective. Signal Processing, 85(11), 2063–2064.
  • Gysels, E., Renevey, P., & Celka, P. (2005). SVM-based recursive feature elimination to compare phase synchronization computed from broadband and narrowband EEG signals in Brain-Computer Interfaces. Signal Processing, 85(11).
  • Gysels, E., & Celka, P. (2004). Phase Synchronization for the recognition of mental tasks in a brain computer interface. IEEE Trans. Neur. Syst. and Rehab. Eng., 12, 406–415.
  • Celka, P., Verjus, C., Vetter, R., Renevey, P., & Neuman, V. (2004). Motion resistant earphone located infrared based heart rate measurement device. In Proceedings of the IASTED International Conference on Biomedical Engineering.
  • Renevey, P., Vetter, R., Krauss, J., Celka, P., & Depeursinge, Y. (2001). Wrist-located pulse detection using IR signals, activity and nonlinear artifact cancellation. In 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Vol. 3, pp. 3030–3033).
  • Celka, P., Vesin, J.-M., Vetter, R., Grueter, R., Thonet, G., Pruvot, E., Scherrer, U. (2001). Parsimonious modeling of biomedical signals and systems: application to the cardiovascular system. In M. Akay (Ed.), Nonlinear biomedical signal processing: Part II. IEEE Press.
  • Vetter, R., Vesin, J.-M., Virag, N., Celka, P., & Scherrer, U. (2000). Observer of autonomic cardiac outflow based on blind source separation of ECG parameters. IEEE Trans. Biomed. Eng., 47, 578–582.
  • Vetter, R., Vesin, J. M., Celka, P., & Scherrer, U. (1999). Observer of the human cardiac sympathetic nerve activity using noncausal blind source separation. IEEE Transactions on Bio-Medical Engineering, 46(3), 322–330.
  • Celka, P., Vetter, R., Vesin, J.-M., Pruvot, E., & Scherrer, U. (1998). Exponential-type distribution of human muscle sympathetic nerve activity results in an automatic quantification method. Computers in Biology and Medicine, 28, 627–637.
  • Stavrev, S., Vesin, J.-M., & Celka, P. (1998). Cardiovascular system modeling in a 3-D state space. Proceedings of NOLTA98, 1, 133–136.
  • Vetter, R., Celka, P., Vesin, J.-M., & Scherrer, U. (1998). Sub-signal extraction of RR times series using independent component analysis. Proceedings of EMBS98, 1, 286–289.
  • Vetter, R., Celka, P., Vesin, J. M., Thonet, G., Pruvot, E., Fromer, M., Bernardi, L. (1998) Subband modeling of the human cardiovascular system: new insights into cardiovascular regulation. Annals of Biomedical Engineering, 26(2), 293–307.
  • Celka, P., Vetter, R., Scherrer, U., & Pruvot, E. (1996). Closed loop heart beat interval modelization in humans using mean blood pressure, instantaneous lung volume and muscle sympathetic nerve activity. In Annual International Conference of the IEEE Engineering in Medicine and Biology – Proceedings (Vol. 4).
  • Celka, P., Vetter, R., Pruvot, E., Scherrer, U., & Karrakchou, M. (1996). Analysis of the relationships between muscle sympathetic nerve activity and blood pressure signals using subband multiinput modeling. Biomedical Engineering – Applications, Basis and Communications, 8(6).
  • Celka, P. (1996). Neuronal based baroreceptor model. In Annual International Conference of the IEEE Engineering in Medicine and Biology – Proceedings (Vol. 5).
  • Celka, P. (1996). Analysis of the relationship between muscle sympathetic nerve activity and blood pressure in humans using linear and nonlinear modelization. Medical and Biological Engineering and Computing, 34(SUPPL. 1).

SATHeart Team