EDA and Activity Sensor
The best tool for measuring electrodermal and physical activity in everyday life!
EdaMove 4 - EDA and Activity Sensor
It has never been so easy to capture electrodermal activity and movement data quickly and precisely in everyday life!
The EdaMove 4 combines excellent signal acquisition with unsurpassed convenience, a benefit for both participants and researchers alike. Begin your study assured in the quality of your data's fitness for publication.
High precision
Obtain precise data from our advanced device platform, capturing a multitude of signals at research level quality. Benefit from our tested and validated algorithms or conduct your own analysis from the raw data.
Whatever your approach, our sensors make data acquisition in every-day life easy and efficient. All the data you need, from when you need it.
Everyday life and real time
Analyse your participants in their every-day life with extensive measurement durations.
In addition, movisens offers the unique option of sensor coupling for all our sensors. Whilst recording the participants physiology, our sensors analyze physiological parameters and transmit the results via Bluetooth to a smartphone equipped with movisensXS. Algorithms within movisensXS process this data and can trigger a questionnaire for the participant when the set conditions occur. If you want to investigate physiological changes such as a high level of activity or skin conductance, such events can act as triggers for queries within the study.
Multimodal data analysis
Combine your activity data with experience sampling data.
The EdaMove 4 offers researchers superior flexibility as our analysis algorithms extract accurate activity parameters from a variety of wearing positions. This allows you to find the most convenient solution for your participants and your study. To get the most out of the raw data captured by the sensor, most researchers prefer to analyze it using the movisens DataAnalyzer's, AI-based, validated algorithms.
Benefit from our many years of experience in the field of ambulatory assessment and let us put together the right analysis solution for you
Our EdaMove 4 is used in the following areas
EDA Monitoring
- EDA measurement in everyday life
- EDA and activity measurements
- EDA and heart rate variability measurements
Recommendations for EDA Monitoring
Interactive Ambulatory Assessment
- EDA measurement and experience sampling
- Combining different sensor parameters
- Trigger algorithms
Recommendations for Interactive Ambulatory Assessment
Look and Feel - The valid and reliable EDA measurement with movisens
Matching products and services
Useful Information
Raw data and live data
Raw data
Also known as primary data, this is obtained directly during an observation, measurement or data collection and remains unprocessed. It represents the original information recorded by sensors. Raw data from acceleration, ECG, and EDA are usually displayed as graphs. Calculating output parameters such as HR, steps, and energy expenditure from these raw signals requires algorithms fit for purpose.Advantage:
Raw data allows long term storage and the implementation of new analysis methods, e.g. for a new algorithm, new AI and it can also be fed into other software.
Disadvantage:
They contain a large amount of data and require more storage space.
Live data
In addition to offline calculation, the EdaMove 4 allows the live analysis of skin conductance and physical activity parameters in conjunction with movisensXS. In live mode, Movement Acceleration, Step Count, and Body Position can be measured, calculated and transmitted via the Bluetooth Smart interface at the rate of 1 value per minute.Technical Data
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Power supply |
Lithium-Polymer-Battery |
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Battery voltage |
3,7 V |
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Number of charging cycles |
300 (with 1C/1C > 80%) |
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Internal memory |
4 GB |
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Maximum recording capacity |
4 Wochen |
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Battery run time |
~ 4 days |
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Recharging time |
~ 1 hour |
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Size of sensor (W x H x D) |
62,3 mm x 38,6 mm x 11,5 mm |
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Weight of sensor |
26 g |
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Protection rate |
Waterproof (IP64) |
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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 |
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Live analysis |
Skin Conductance Level Movement Acceleration Step count |
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Indicators |
LED, 3-color Vibration alarm |
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User Interfaces |
Marker (tapping) |
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Interfaces |
Micro-USB, Bluetooth Smart (4.0) |
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API |
Java API für USB (Windows) Example for Bluetooth Smart (Android) |
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Wear locations |
Wrist, Ankle |
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Wearing systems |
Wrist Band |
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Environmental conditions |
Temperature: -20 °C - 60 °C 0 °C - 45 °C during charging Atmospheric pressure: 300 to 1200 hPa absolute |
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Warranty |
2 years |
Literature and Validation
- User Acceptance in Automated Vehicles: An Investigation of Electrodermal Activity Using Wearables.
- Monitoring audience engagement using electrodermal activity during an inaugural lecture.
- Predicting experiences of paranoia and auditory verbal hallucinations in daily life with ambulatory sensor data – A feasibility study.
- Effect of task nature during short digital deprivation on time perception and psychophysiological state.
- Virtual Reality-Based Approach to Evaluate Emotional Everyday Scenarios for a Digital Health Application.
- The effect of social anxiety on social attention in naturalistic situations.
- A momentary approach to understanding subjective well-being: Daily motives, personality, and affect.
- Evaluating Team Workload Through Physiological Synchrony: An Exploratory Study Using MdRQA Data to Assess Teams in Action.
- Applying artificial intelligence on EDA sensor data to predict stress on minimally invasive robotic-assisted surgery.
- The use of music for Solace, its connection to Openness and its moderating effects on music listening and stress.
- Studying the Influence of Single Social Interactions on Approach and Avoidance Behavior – A Multimodal Investigation in Immersive Virtual Reality.
- Seven robust and easy to obtain biomarkers to measure acute stress.
- Social Conditioning in Immersive Virtual Reality Elicits a Hypervigilant-Avoidant Response Pattern.
- Predicting the onset of psychotic experiences in daily life with the use of ambulatory sensor data – A proof-of-concept study.
- 3. OBJECTIVE ANALYSIS AND COMPARISON OF STRESS LEVEL DURING ROBOTIC AND CONVENTIONAL LAPAROSCOPIC SURGERY.
- Physiological synchrony in brain and body as a measure of attentional engagement.
- Understanding the combined effects of sleep deprivation and acute social stress on cognitive performance using a comprehensive approach.
- Analysis of EDA and Heart Rate Signals for Emotional Stimuli Responses.
- Human uncertainty in interaction with a machine: establishing a reference dataset.
- The connection between stress, density, and speed in crowds.
- Approaches, Applications and Challenges in Physiological Emotion Recognition—A Tutorial Overview.
- Untersuchungen zur Integration objektiver Messgrößen in ein Virtual-Reality-Studiendesign zur Evaluation subjsubjekt Eindrücke von Fahrzeuginnenräumen.
- Pedestrian Crowd Management Experiments: A Data Guidance Paper.
- Physiological and neural synchrony in emotional and neutral stimulus processing: A study protocol.
- Robustness of Physiological Synchrony in Wearable Electrodermal Activity and Heart Rate as a Measure of Attentional Engagement to Movie Clips.
- Tranquillity, transcendence, and retreat: the transformative practice of listening at Evensong.
- At Crossroads in a Virtual City: Effect of Spatial Disorientation on Gait Variability and Psychophysiological Response among Healthy Older Adults.
- The Effects of Stimulus Duration and Group Size on Wearable Physiological Synchrony.
- Can Music-evoked autobiographical memories be triggered through music recommendation.
- Waiting Behavior and Arousal in Different Levels of Crowd Density: A Psychological Experiment with a “Tiny Box”.
- Current trends and opportunities in the methodology of electrodermal activity measurement.
- Validation of wearables for electrodermal activity (EdaMove) and heart rate (Wahoo Tickr).
- Heart rate variability, postural sway and electrodermal activity in competitive golf putting.
- How does it feel to walk in Berlin? Designing an Urban Sensing Lab to explore walking emotions through EDA sensing.
- Assessing the difficulty of annotating medical data in crowdworking with help of experiments.
- Towards the Applicability of Measuring the Brain Activity in the Context of Process Model Comprehension.
- Moments that matter? On the complexity of using triggers based on Skin Conductance to sample arousing events within an Experience Sampling Framework.
- Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios.
- Social anxiety is associated with heart rate but not gaze behavior in a real social interaction.
- Measuring Behavior 2020-21.
- Physiological synchrony in EEG, electrodermal activity and heart
rate reflects shared selective auditory attention. - A Comparison between Laboratory and Wearable Sensors in the Context of Physiological Synchrony.
- A Usability Study of Physiological Measurement in School Using Wearable Sensors.
- Using Virtual Reality Scenarios Along With Physiological Measures as Intervention Procedure in Patients With Dementia.
- Applicability of Immersive Analytics in Mixed Reality: Usability Study.
- Electrodermal activity patterns in sleep stages and their utility for sleep versus wake classification.
- A mixed-methods study of physiological reactivity to domain-specific problem solving: methodological perspectives for process-accompanying research in VET.
- Estudo piloto em câmara climática: efeito da luz natural em aspectos de saúde e bem-estar não relacionados à visão.
- Detecting cognitive underload in train driving: A physiological approach.
- Mobile Sensors for Multiparametric Monitoring in Epileptic Patients.
- A personalized and reconfigurable cyberphysical system to handle multi-parametric data acquisition and analysis for mobile monitoring of epileptic patients.
- Evaluation of environmental effects on the measurement of electrodermal activity under real-life conditions.
- Komfortgewinn für Passagiere auf Langstreckenflügen durch den Einsatz chronobiologisch angepasster LED-Kabinenbeleuchtung.
- Publication recommendations for electrodermal measurements.
All publications can be find here.