ECG and Activity Sensor

movisens ekgMove is a psycho physiologic ambulatory measurement system - designed for research applications.

The sensor acquires raw data of a single channel ECG, 3D acceleration, barometric air pressure and temperature for up to 2 weeks

From this data secondary parameters like heart rate, heart rate variability, steps, activity classes, and energy expenditure (Excel) can be calculated with the movisens DataAnalyzer software as well as meaningful reports (PDF).

The sensor can be used with a chest strap (available in size XS, S, M, L, XL) as well as with adhesive one way electrodes.





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ECG and Activity Sensor ekgMove, front

 


Top features

  • Combination of ecg and physical activity sensor in one tiny system
  • Comfortable chest strap with perfect signal quality for long-term measurements (up to 2 weeks), no annoying electrode cables
  • Exact and validated energy expenditure calculation and activity recognition
  • Sustainable data due to open file format
  • Operation optimized for studies
  • Open interfaces: SDK for Bluetooth and USB

Applications

  • Mobile ECG long-term monitoring
  • Mobile long-term monitoring of heart rate and heart rate variability
  • Study of the autonomic nervous system (ANS)
  • Behavioral monitoring
  • Psycho physiologic stress monitoring
  • Energy expenditure calculation and activity recognitioning
  • Psycho-neuro-immunology
  • Affective computing
  • Integration in complex monitoring systems

Matching products and services

DataAnalyzer Software, Box

DataAnalyzer Software for the analysis of sensor data

Accessories
and Consumables for the sensors

movisens XS Smartphone-based e-Diary with experience sampling

Downloads

Software
Documentation
Data examples
Reports
External Tools

Technical data

Power supply

Lithium-Ion battery

Supply voltage

3 V

Battery voltage

2,7 - 4,2 V

Number of charging cycles

300 with 1C/1C > 80%

Maximum recording capacity

At least 2 weeks, depending on firmware configuration

Battery run time (recording, Bluetooth off)

~ 2 days

Size of sensor

(W x H x D)

62,3mm x 38,6mm x 10,5mm

Weight of sensor

23,2g

Internal sensors

ECG-Amplifier:

Resolution: 12bit, Input range CM=560mV, DM=+/-5mV, Gain 227,

3db bandwidth 1,6 to 33Hz

Output rate: 256Hz to 1024Hz

 

3D acceleration sensor:

Measurement range: +/- 8 g

Noise: 4 mg

Output rate: 64 Hz

 

Pressure sensor:

Measurement range: 300 - 1100 hPa

Noise: 0,03 hPa

Output rate: 1 Hz

Indicators

LED, 3-color

(operation and charging status)

Vibrating alert (start and end of measurement)

Interfaces

Micro-USB, Bluetooth

Environmental conditions

Temperature:

-20 °C to 60 °C

0 °C to 45 °C during charging

 

Humidity:

0 to 75% RH relative humidity

 

Atmospheric pressure:

300 to 1100 hPa absolute

Literature

  • Physical Activity and Affective Well-Being in Everyday Life Comparing Sport Activities and Daily Physical Activities Regarding Acute and Sustainable Associations.
    Stephanie Jeckel & Gorden Sudeck (2016) in: Zeitschrift für Gesundheitspsychologie (24).
  • Prolonged Non-metabolic Heart Rate Variability Reduction as a Physiological Marker of Psychological Stress in Daily Life.
    Bart Verkuil & Jos F Brosschot & Marieke S Tollenaar et al. (2016) in: Annals of Behavioral Medicine. Read more...
  • Resource Efficient Data Compression Algorithms for Demanding, WSN based Biomedical Applications .
    Christos P. Antonopoulos & Nikolaos S. Voros (2015) in: Journal of Biomedical Informatics . Read more...
  • Mobile Sensors for Multiparametric Monitoring in Epileptic Patients.
    Stefan Hey & Panagiota Anastasopoulou & André Bideaux et al. (2015) in: Cyberphysical Systems for Epilepsy and Related Brain Disorders: Multi-parametric Monitoring and Analysis for Diagnosis and Optimal Disease Management. Read more...
  • Real-Time Management of Multimodal Streaming Data for Monitoring of Epileptic Patients.
    Dimitrios Triantafyllopoulos & Panagiotis Korvesis & Iosif Mporas et al. (2015) in: Journal of Medical Systems (40). Read more...
  • Does a 20-week aerobic exercise training programme increase our capabilities to buffer real-life stressors? A randomized, controlled trial using ambulatory assessment.
    Birte von Haaren & Joerg Ottenbacher & Julia Muenz et al. (2015) in: European Journal of Applied Physiology. Read more...
  • Integrating biosignals into information systems: A NeuroIS tool for improving emotion regulation.
    Philip J. Astor & Marc T. P. Adam & Petar Jerčić et al. (2014) in: Journal of Management Information Systems (01).
  • A personalized and reconfigurable cyberphysical system to handle multi-parametric data acquisition and analysis for mobile monitoring of epileptic patients.
    A. Bideaux & P. Anastasopoulou & S. Hey et al. (2014) in: Sensing and Control S&C BArcelona, Spain. Read more...
  • Study protocol: psychological and physiological consequences of exposure to mass media in young women-an experimental cross-sectional and longitudinal study and the role of moderators.
    Simone Munsch (2014) in: BMC Psychology (2). Read more...
  • Comparing Objective and Subjective Methods to Support Reflective Learning: an Experiment on the Influence on Affective Aspects.
    Verónica Rivera-Pelayo & Marc Kohaupt (2014). Read more...
  • Emotions and Emotion Regulation in Economic Decision Making.
    Philipp J. Astor (2013). Read more...
  • Design and Evaluation of Affective Serious Games for Emotion Regulation Training.
    Petar Jercic (2013).
  • Komfortgewinn für Passagiere auf Langstreckenflügen durch den Einsatz chronobiologisch angepasster LED-Kabinenbeleuchtung.
    A. Leder & J. Krajewski & S. Schnieder (2013) in: Deutscher Luft- und Raumfahrtkongress 2013, Stuttgart. Read more...
  • A Biofeedback Game for Training Arousal Regulation during a Stressful Task: The Space Investor.
    Olle Hilborn & Henrik Cederholm & Jeanette Eriksson et al. (2013) in: Human-Computer Interaction. Towards Intelligent and Implicit Interaction (8008). Read more...
  • Measuring emotional arousal for online applications: Evaluation of ultra-short term heart rate variability measures.
    Kristina Schaaff & Marc T. P. Adam (2013) in: International Conference on Affective Computing and Intelligent Interaction (ACII).
  • Enhancing mobile working memory training by using affective feedback..
    K. Schaaff (2013) in: IADIS International Conference on Mobile Learning, 14-16 March 2013, Lisbon, Portugal, 2013, Conference Proceedings pp. 269-273..
  • Mobile sensor systems for measurement of stress and physical activity in preventive healthcare applications.
    S. Hey (2012).
  • A Serious Game using Physiological Interfaces for Emotion regulation Training in the Context of Financial Decision-Making..
    Petar Jercic & Philipp J Astor & Marc Thomas Philipp Adam et al. (2012) in: Presented at European Conference of Information Systems (ECIS 2012), Barcelona, Spain, 10-13 June 2012. Read more...
  • An approach to automotive ECG measurement validation using a car-integrated test framework.
    Johannes Schneider & Christian Koellner & Stephan Heuer (2012) in: Intelligent Vehicles Symposium (IV), 2012 IEEE. Read more...
  • Motivation and User Acceptance of Using Physiological Data to Support Individual Reflection.
    A. Fessl & V. Rivera-Pelayo & L. Müller et al. (2011) in: 2nd International Workshop on Motivational and Affective Aspects in Technology Enhanced Learning (MATEL 11). Read more...
  • Estimation of energy expenditure using accelerometers and activity-based energy models - validation of a new device.
    S. Härtel & J. P Gnam & S. Löffler et al. (2011) in: European Review of Aging and Physical Activity (Volume 8). Read more...
  • User Study: Motivation and User Acceptance of Using Physiological Data to Support Individual Reflection..
    Angela Fessl & Verónica Rivera-Pelayo & Lars Müller et al. (2011).
  • From Stress Awareness to Coping Strategies of Medical Staff: Supporting Reflection on Physiological Data.
    Lars Müller & Veronica Rivera Pelayo & Christine Kunzmann et al. (2011) in: Second International Workshop on Human Behavior Understanding HBU 2011. Read more...
  • Einsatz sensorgestützter Verfahren im Gesundheitswesen: Herausforderungen und Lösungsansätze.
    D.I.D.S. Saboor & M.F.H.M. Schallhart (2011). Read more...
  • Sensor Chest Strap Wirelessly Coupled with an e-Diary for Ambulatory Assessment of Psycho-Physiological Data.
    Jürgen Stumpp & Panagiota Anastasopoulou & Hatem Sghir et al. (2011) in: Assessing Real-World Impact of Clinical Interventions and Outcomes.
  • Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology..
    (1996) in: Circulation (93).

You can find more publications here.