As part of the new sensor generation, the EdaMove 4 takes the proven qualtiy of the EdaMove 3 and incorporates the most sought after improvements from extensive discussions with researchers in the field.


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 EdaMove 4's research capabilities. All the while remaining the best choice for researcher's requiring high quality ambulatory EDA and physical activity data.

The EdaMove 4 provides researchers with the most comprehensive tool for recording and analysing Electrodermal (Galvanic Skin Response) and physical activity. The sensor combines our world-class 4th generation accelerometer, a high-quality EDA sensor and a Bluetooth Smart interface that allows the sensor to interact with our Experience Sampling platform, movisensXS to trigger questionnaires based on changes in physiological parameters.

Capable of capturing up to 4 weeks of data, the EdaMove 4 allows researchers to isolate and understand emotional affect with greater clarity than before. A new electrode based attachment system ensures an efficient and durable connection, recording a high quality signal with minimal effort. In addition to the EDA signal that allows the caluclation of secondary parameters like skin conductance level (SCL) and skin conductance responses (SCR), the sensor acquires the raw data of the 3D acceleration of a participant, thus also allowing the calculation of activity parameters such as activity intensity with the movisens DataAnalyzer.

The additional recording of angular rate, temperature and barometric air pressure enable the swift discovery of and isolation of many of the typical artifacts that plague EDA data captured by standard ambulatory measurement systems. The EdaMove 4 connects to a comforable textile band worn on either the wrist or ankle, increasing participant comfort and compliance, and also providing greater measurement quality for researchers.



Top-Features

  • New design with new carrying systems in a waterproof housing
  • Advanced data acquisition through integrated gyroscope
  • New acceleration sensor with higher resolution
  • Meets all relevant EDA standards
  • Live analysis of measurement data
  • Improved data transfer via Bluetooth Smart interface
  • 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 EDA (elecrodermal activity) / GSR (galvanic skin response)
  • Psycho physiologic monitoring
  • Research of the autonomic nervous system (ANS)
  • Behavioral monitoring
  • Clinical Psychology
  • Affective Computing


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Downloads

Software
Documentation
External Tools

Technical Data

Power supply

Lithium-Polymer-Battery

Battery voltage

3,7 V

Number of charging cycles

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

Internal memory

4 GB

Maximum recording capacity

4 Weeks

Battery run time

~ 4 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

EDA Sensor:

Exosomatic method, constant voltage, DC, 0,5 V

Resolution: 14 bit, Input range 2 µS -100 µS

Bandwith: DC - 8 Hz

Output rate: 32 Hz

3D acceleration sensor:

Measurement range: +/- 16 g

Output rate: 64 Hz

Rotation rate Sensor:

Measurement range: +/-2000 dps

Resolution: 70 mdps

Output rate: 64 Hz

Pressure sensor:

Measurement range: 300 - 1100 hPa

Resolution: 0,03 hPa

Output rate: 8 Hz

Temperature sensor:

Output rate: 1 Hz

Live analysis

Skin Conductance Level

Movement Acceleration

Step count

Indicators

LED, 3-color

Vibration alarm

User Interfaces

Marker (tapping)

Interfaces

Micro-USB, Bluetooth Smart (4.0)

API

Java API für USB (Windows)

Example for Bluetooth Smart (Android)

Wear locations

Wrist, Ankle

Wearing systems

Wrist Band

Environmental conditions

Temperature:

-20 °C - 60 °C

0 °C - 45 °C during charging

Atmospheric pressure:

300 to 1200 hPa absolute

Warranty

2 years

Literature und Validation

  • 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...
  • Electrodermal activity patterns in sleep stages and their utility for sleep versus wake classification.
    Anne Herlan & Jörg Ottenbacher & Johannes Schneider et al. (2018) in: Journal of sleep research. Read more...
  • A mixed-methods study of physiological reactivity to domain-specific problem solving: methodological perspectives for process-accompanying research in VET.
    Tobias Kärner (2017) in: Empirical Research in Vocational Education and Training (9). Read more...
  • Estudo piloto em câmara climática: efeito da luz natural em aspectos de saúde e bem-estar não relacionados à visão.
    Cintia Akemi Tamura & Eduardo Leite Krüger (2016) in: Ambiente Construído (16). Read more...
  • Detecting cognitive underload in train driving: A physiological approach.
    Dan Basacik & Sam Waters & Nick Reed (2015). 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...
  • 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...
  • Evaluation of environmental effects on the measurement of electrodermal activity under real-life conditions.
    Dorothee Kapp & Kristina Schaaff & Jörg Mathias Ottenbacher et al. (2014) in: Biomedical Engineering / Biomedizinische Technik (59).
  • 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...
  • Publication recommendations for electrodermal measurements.
    WALTON T ROTH & MICHAEL E DAWSON & DIANE L FILION (2012) in: Psychophysiology (49).

You can find more publications here.