Capture the answers when it matters – SensorTrigger

Now it’s finally possible… capturing Experience Sampling data in sync with physiological parameters!

Previously discovering any relationships between physiological and subjective data would require cross referencing the information after the study. What if we said you can now detect heart rate and have it trigger a form? Or even psychological stress? Or you’d like to track Activity Levels? We’ve got you covered with that and more…

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Upcoming Events

To learn how sensor triggering can unlock greater insights in your research visit our stand at the following conferences:

New white paper available

We've just added a few white papers to our website that we thought you may find interesting.

Energy Expenditure

First is a validation paper on the energy expenditure calculation of the Move II (now superceded by the Move 3). Some manufacturers are still utilising basic linear regression models to calculate the energy expeniture in their activity sensors. This paper demonstrates the advantages of utilising an activity class based algorithm vs. a basic linear regression to obtain a more accurate estimation of energy expenditure. It's somewhat old news, but it's good to remind everyone occasionaly of the superiority of our activity based method over the basic linear regression model.

White Paper Move II Validation Energy Expenditure

R-Peak Detection

Secondly we have a validation of the R-peak detection capabilities of the EkgMove (now superceded by the EcgMove 3). This paper puts the EkgMove through it's paces by introducing movement artefacts and validating the detection capabilities in reference to the Somnoscreen plus.

White Paper Validity of R-Peak Detection


The measurement of arousal using Electro Dermal Activity (Galvanic Skin Response) is often hindered by factors like movement, temperature and exercise. This paper highlights the benefits of capturing activity data in addition to EDA/GSR. It details a method that can isolate the emotional arousal component of EDA/GSR using our EdaMove sensor.

White paper EdaMove Effects of Stimuli

Light and Activity Sensor LightMove 3

We took our acclaimed accelerometer technology and added 5 channels of light detection (Red, Green, Blue, Clear, IR) to develop our newest solution for ambulatory assessment:
Light and Activity Sensor LightMove 3

Capable of recording ambient light, 3D acceleration, temperature, and barometric air pressure data for up to two months, our sensor is ideal for research into the effect of light exposure and physical activity in the fields of:

  • Depression
  • Sleep analysis
  • Circadian rhythms
  • Shift work
  • Behavioral monitoring


  • The ability to easily calculate parameters like activity class, steps, energy expenditure, light irradiance or illuminance
  • Integrated Bluetooth Smart allowing live transmission of data calculated on the sensor
Click here for more features!

Upcoming Events

For a personal demonstration of the LightMove3 visit our stand at the following conferences:

Interactive Ambulatory Assessment – Project

Dr. Verkuil & Dr. Brosschot from Leiden University will use heart rate variability (HRV) to investigate the impact of psychological stress on physiological stress. It is therefore important to measure the psychological stress at moments when people are also likely to be physiologically stressed. In their project, all periods of HRV that are not explained by physical activity will be detected. Each non-metabolic induced HRV decrease period will trigger a smartphone app that asks subjects to indicate what they are currently thinking and doing and how they are currently feeling. The aim of this study is to test if stress cognition is increased during periods of HRV decrease compared to random neutral episodes. Leiden University realizes this highly innovative project using movisens ecgMove 3 and movisensXS.