Als Teil der neuen Sensorgeneration verbindet der EKG- und Aktivitätssensor EcgMove 4 die bisherigen Vorzüge des bewährten EcgMove 3 mit den Verbesserungen der 4. Generation, bei der es uns gelungen ist, zahlreiche Anforderungen von Forschern zu berücksichtigen, deren Wünsche umzusetzen und somit die Qualität der Sensoren noch weiter zu erhöhen.


Die Sensoren der 4. Generation bieten Ihnen unter anderem folgende Vorteile:

  • Neues Design mit optimierter Handhabung: Das neue Gehäuse bietet nicht nur ein schickes Design, sondern auch viele praktische Vorteile. Die Sensoren sind wasserdicht und schmutzabweisend, und durch die verbesserten Tragesysteme einfacher, flexibler und sicherer in der Anwendung.
  • Mehr Möglichkeiten der Datenerfassung: Durch den Einsatz neuester Technologien verfügen nun alle Sensoren der 4. Generation zusätzlich über ein Gyroskop (Drehratensensor).
  • Verbesserte Analysefähigkeiten: Ein weiterer großer Benefit wird durch den neuartigen Beschleunigungssensor erzielt, der jetzt mit einer noch höheren Auflösung die Messdaten aufzeichnet. Dadurch werden vor allem bei der Analyse von sedentärem Verhalten und der Ablageerkennung signifikante Verbesserungen der Ergebnisse erreicht.
  • Erhöhte Datensicherheit: Der neue Bluetooth-Buffer auf dem Sensor sorgt dafür, dass bei Verbindungsunterbrechung die Daten zwischengespeichert und, sobald die Verbindung wieder besteht, direkt übertragen werden; somit ist eine lückenlose Datenaufzeichnung gewährleistet.
  • Erweiterte Anwendungsbereiche: Durch die genannten Verbesserungen ist der EcgMove 4 nun auch für eine Reihe zusätzlicher Anwendungen einsetzbar.

Der EcgMove 4 ist der genauste mobile Sensor zur Ermittlung des EKG-Signals in Kombination mit körperlicher Aktivität, der Langzeitmessungen ohne störende Kabel ermöglicht. Die Kombination dieser beiden Parameter ermöglicht es in wenigen Schritten Rückschlüsse auf das Verhalten, die Aktivität, die Funktionsfähigkeit des Herzens sowie des vegetativen Nervensystems zu ziehen.

Durch die parallele Aufzeichnung und Speicherung der Rohdaten (EKG-Signal, 3-Achsen-Beschleunigung, Drehrate, Luftdruck und Temperatur) über einen Zeitraum von bis zu 2 Wochen gehen keine Daten verloren und können nach Belieben im Anschluss weiterverarbeitet werden. Die gemessenen Rohdaten können zudem live auf dem Sensor analysiert werden um sie mittels einer Bluetooth-Smart-Schnittstelle einfach z.B. auf ein Smartphone zu übertragen.

Der EcgMove 4 ist optimiert für den Einsatz in wissenschaftlichen Studien und für das interaktive ambulante Assessment. Die neuen Tragesysteme mittels Brustgurt oder Klebeelektroden bieten gleichzeitig einen hohen Tragekomfort, was zu einer verbesserten Compliance bei den Probanden, einer höheren Datenqualität und dadurch zu verringertem Aufwand in der Durchführung einer Studie und geringeren Kosten führt.

Mit Hilfe der Analyse-Software DataAnalyzer können ohne großen Aufwand Ausgabeparameter wie Herzfrequenz, Herzratenvariabilität, Aktivitätsklassen, Schritte, Energieumsatz und Metabolische Äquivalente (MET) berechnet und aussagekräftige Berichte (PDF) erzeugt werden.



Top-Features

  • Neues Design mit neuen Tragesystemen im wasserdichten Gehäuse
  • Erweiterte Datenerfassung durch integriertes Gyroskop
  • Neuer Beschleunigungssensor mit höherer Auflösung
  • Anlageerkennung zum automatischen Start der Messung
  • Live Analyse der Daten auf dem Sensor
  • Verbesserte Datenübertragung über Bluetooth-Smart Schnittstelle
  • Kombination von EKG- und Aktivitätsmessung in einem System
  • Exakte und validierte Energieumsatzbestimmung und Erkennung von Alltagsaktivitäten
  • Java API für USB (Windows)
  • API: Beispielimplementierung für Bluetooth Smart (Android)

Anwendungen

  • Interaktives Ambulantes Assessment
  • Mobiles Langzeit-Monitoring von Herzrate und Herzratenvariabilität
  • Untersuchung des vegetativen Nervensystems
  • Verhaltensmonitoring
  • Psycho-physiologisches Belastungs-Monitoring
  • Energieumsatzschätzung und Aktivitätserkennung
  • Affective Computing
  • Integration in komplexe Systeme

Dazu passende Produkte und Dienstleistungen

Downloads

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  • Wir arbeiten ständig an der Weiterentwicklung unserer Produkte. Damit Sie diese Verbesserungen nutzen können, informieren wir Sie mit unserem Newsletter regelmäßig darüber. Bitte melden sie sich hier dazu an.
Software
Dokumentation
Externe Tools

Technische Daten

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

2 years

Literatur und Validierung

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  • Does a 20-week aerobic exercise training programme increase our capabilities to buffer real-life stressors? A randomized, controlled trial using ambulatory assessment.
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  • Integrating biosignals into information systems: A NeuroIS tool for improving emotion regulation.
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  • A personalized and reconfigurable cyberphysical system to handle multi-parametric data acquisition and analysis for mobile monitoring of epileptic patients.
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  • 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...
  • 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..
  • Design and Evaluation of Affective Serious Games for Emotion Regulation Training.
    Petar Jercic (2013).
  • 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.
    P. Jercic & P. J. Astor & M. T. P. 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...
  • 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.
    A. Fessl & V. Rivera-Pelayo & L. 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...
  • 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...
  • 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).

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