As part of the new sensor generation, the EcgMove 4 activity sensor combines the previous benefits of the proven EcgMove 3 with the 4th generation enhancements, allowing us to address a wide range of researchers' needs, implement their requests, and further enhance the quality of the sensors. Thus, the EcgMove 4 strengthens it's position as the go to device for researchers who care about high quality ECG and Activity data.


The 4th sensor generation offers researchers numerous advantages, including:

  • New design for optimal handling: The improved case offers a sleek design aesthetic offering many practical advantages. The waterproof and dirt-repellent housing coupled with the improved carrying systems make the sensors simpler, more versatile and safer to use.
  • More data collection capabilities: Thanks to the integration of the latest technologies, the 4th generation sensors now incorporate a Gyroscope (Angular Rate Sensor).
  • Improved analysis possibilities: Our highly acclaimed acceleration sensor also received an overhaul, and now records the measurement data at an even higher resolution. Consequently, we’ve achieved significant improvements in the obtainable results, especially in the analysis of sedentary behavior and non-wear detection.
  • Increased data retention: A new Bluetooth buffer ensures the preservation of data during disconnection, with the buffered data transferred upon reconnection; thus guaranteeing a continuous data recording at all times.
  • Broader research applications: Already a class leader in quality data acquisition for many research areas, these improvements expand the EcgMove 4's research capabilities. All the while remaining the best choice for researcher's requiring high quality ECG and physical activity data.

The EcgMove 4 follows on from the EcgMove 3 as the most precise sensor for the measurement of ECG combined with physical activity. Capable of long term ambulatory recordings without the inconvenience of cables. Through the parallel recording of the ECG and Activity Signals (ECG, 3D Accelerometer, Gyroscope, Barometric Air Pressure, and Temperature), the EcgMove 4 offers a rich treasure trove of data for the detailed analysis of the functioning of the heart, the autonomic nervous system, and additionally behaviour and activity. Whilst recording the raw data stream, the sensor can also analyze certain parameters live on the sensor and transmit the results via Bluetooth smart interface, e.g. to a smartphone.

The sensor is optimized for use in scientific studies and interactive ambulatory assessment. The new attachment systems offer you great flexibility in use and a high wearing comfort for the study participant, with the choice of adhesive electrodes or our acclaimed dry electrode textile chest belt. This leads to improved compliance, higher data volume and quality, and thus reduces the effort of carrying out a study and reduces costs.

Combined with our Analysis-Software DataAnalyzer allows the simple calculation of parameters such as Heart Frequency, Heart Rate Variability, Activity Class, Steps, Energy Expenditure and Metabolic Equivalent of Task (MET).



Top-Features

  • New design with new carrying systems in a waterproof housing
  • Advanced data acquisition through integrated gyroscope
  • New acceleration sensor with higher resolution
  • Attachment detection for automatically starting a measurement
  • Live analysis of measurement data
  • Improved data transfer via Bluetooth Smart interface
  • Combination of ECG- and Activity measurement in a single system
  • Exact and validated Energy Expenditure calculations and detection of everyday activities
  • Java API for USB (Windows)
  • API: Example implementation for Bluetooth Smart (Android)

Applications

  • Interactive Ambulatory Assessment
  • Mobile long term monitoring of Heart rate and Heart Rate Variability
  • Examination of the Autonomic Nervous System
  • Behavioural Monitoring
  • Psycho-physiological Stress-Monitoring
  • Energy Expenditure Calculation and Activity Recognition
  • Affective Computing
  • Integration in complex systems

Matching products and services

Downloads

Software
Documentation
External Tools

Technical Data

Power supply

Lithium-Polymer-Battery

Battery voltage

3,7 V

Number of charging cycles

300 (with 1 C / 1 C > 80%)

Internal memory

4 GB

Maximum recording capacity

2 weeks

Battery run time

~ 3 days

Recharging time

~ 1 hour

Size of sensor (W x H x D)

62,3 mm x 38,6 mm x 11,5 mm

Weight of sensor

26 g

Protection rate

Waterproof (IP64)

Internal sensors

ECG sensor:

Resolution: 12 bit, Input range CM = 560 mV, DM = +/-5 mV, 3db bandwidth 1,6 - 33 Hz

Output rate: 1024 Hz

 

3D acceleration sensor:

Measurement range: +/- 16 g

Output rate: 64 Hz

 

Rotation rate sensor:

Measurement range: +/-2000 dps

Output rate: 64 Hz

 

Pressure sensor:

Measurement range: 300 - 1100 hPa

Noise: 0,03 hPa

Output rate: 8 Hz

 

Temperature sensor:

Output rate: 1 Hz

Live analysis

Heart Rate

bpmBxB

NN-List

HRV Rmssd

HRV is valid

Movement Acceleration

Step count

Indicators

LED, 3-color

Vibration alarm

User Interfaces

Marker (tapping)

Interfaces

Micro-USB, Bluetooth Smart (4.0)

API

Java API for USB (Windows)

Example for Bluetooth Smart (Android)

Wear locations

Chest

Wearing systems

Chest Belt, adhesive Electrodes

Environmental conditions

Temperature:

-20 °C to 60 °C

0 °C to 45 °C during charging

Atmospheric pressure:

300 to 1200 hPa absolute

Warranty

1 year

Literature und Validation

  • Brute Force ECG Feature Extraction Applied on Discomfort Detection.
    Guillermo Hidalgo Gadea & Annika Kreuder & Carsten Stahlschmidt et al. (2019) in: Information Technology in Biomedicine: Proceedings 6th International Conference, ITIB'2018, Kamień Śląski, Poland, June 18--20, 2018. Read more...
  • Self-reported emotion regulation difficulties are associated with mood but not with the biological stress response to thin ideal exposure.
    Nadine Humbel & Nadine Messerli-Bürgy & Kathrin Schuck et al. (2018) in: PLOS ONE (13). Read more...
  • Energy Expenditure During Incline Walking – Benefits of Integrating a Barometer into Activity Monitors.
    Manuel Armbruster & Panagiota Anastasopoulou & Stefan Altmann et al. (2018) in: American Journal of Sports Science (6). Read more...
  • Paranoid Delusions as an Adaptive Response to Social Evaluative Stress?.
    Annika Clamor & Katarina Krkovic (2018) in: Zeitschrift für Psychologie (226). Read more...
  • Effectiveness of a smartphone-based worry-reduction training for stress reduction: A randomized-controlled trial.
    Anke Versluis & Bart Verkuil & Philip Spinhoven et al. (2018) in: Psychology & Health (0). Read more...
  • An experience sampling study on the nature of the interaction between traumatic experiences, negative affect in everyday life, and threat beliefs.
    Katarina Krkovic & Björn Schlier & Tania Lincoln (2018) in: Schizophrenia Research. Read more...
  • Immediate and sustained effects of intermittent exercise on inhibitory control and task-related heart rate variability in adolescents.
    Sebastian Ludyga & Uwe Pühse & Stefano Lucchi et al. (2018) in: Journal of Science and Medicine in Sport. Read more...
  • Physiological and cognitive performance of exposure to biophilic indoor environment .
    Jie Yin & Shihao Zhu & Piers MacNaughton et al. (2018) in: Building and Environment . Read more...
  • A Data Compression Hardware Accelerator Enabling Long-Term Biosignal Monitoring Based on Ultra-Low Power IoT Platforms.
    Christos P. Antonopoulos & Nikolaos S. Voros (2017) in: Electronics (6). Read more...
  • Sport activities in daily routine.
    Stephanie Jeckel & Gorden Sudeck (2017) in: German Journal of Exercise and Sport Research. Read more...
  • 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.