FAQ
General
The completion of a preliminary study has many advantages and can allow you to minimise potential risks to your main study. As well as a way to check the design of the study (i.e. sensor incorrectly initialised, poor user compliance due to too many questions in surveys, too difficult or not enough options to select, etc), it allows you to optimise the main study. In general a preliminary study allows you to become familiar with the use of the sensor this will allow you to optimise quality of the data obtained.
All Sensors
All sensors of the 4th generation (Move 4, LightMove 4, EcgMove 4, EdaMove 4) are placed into a cradle. The cradle is connected via USB to a PC with SensorManager software installed. This software allows the transfer of the sensor data to the PC.
The measurement data from the sensor and all secondary parameters is recorded in the Unisens Data format. Unisens is a free and open source data format designed to capture the data from multiple sensors. For more information about unisens please visit http://www.unisens.org. A unisens data set consists of a meta file (unisens.xml) and different data files for each measurement signal and every secondary parameter. The secondary parameters are saved within the unisens data.
Yes. You can process the raw data with other software applications such as EDFBrowser, Matlab, or Kubios HRV.
In general, all sensors have a USB interface. Our newest generation of sensors (Move 4, LightMove 4, EcgMove 4, EdaMove 4) come with Bluetooth smart integrated in the design to allow for further integration with our experience sampling platform movisensXS.
The EcgMove 4 ECG and activity sensors have a marker function. When double tapping on the sensor a marker is set. If the sensor sets a marker, this is confirmed by a vibration.
This error can occur when the driver for the sensor was not installed properly during the SensorManager installation. Please uninstall and then re-install the SensorManager and take care that the driver installation is not interrupted.
It is possible to test the sensor for a period of up to three weeks. Since we have a limited quantity of the sensors available for this purpose, please suggest a time period and what sensor you would like to test.
Yes. You can hire our sensors for a weekly fee. Please contact us for a quote on this service.
A measurement is usually performed in six steps:
1) Preparation of the sensor. Ensure that the battery is fully charged.
2) Configure the sensor using the SensorManager software and start the measurement.
3) Complete the measurement.
4) Extract the measurement from the sensor and save the raw data. It’s always good to make a backup of the raw data as your next step.
5) Open the data with the UnisensViewer and make any necessary edits.
6) Analyse the data with DataAnalyzer.
1) Preparation of the sensor. Ensure that the battery is fully charged.
2) Configure the sensor using the SensorManager software and start the measurement.
3) Complete the measurement.
4) Extract the measurement from the sensor and save the raw data. It’s always good to make a backup of the raw data as your next step.
5) Open the data with the UnisensViewer and make any necessary edits.
6) Analyse the data with DataAnalyzer.
Activity Sensor Move 4
The best results will be obtained with the sensor placed on the right hip. It’s also possible to wear the activity sensor on the chest with a chest strap. Be sure to select the correct position when setting up the sensor. The position that the sensor is worn is important information that needs to be entered in to the DataAnalyzer to ensure proper calculations.
ECG and Activity Sensor EcgMove 4
The sensor can be attached to the body in two different ways: with a chest strap or with adhesive electrodes. The data quality remains the same for both options. In contrast to the chest belt, adhesive electrodes can be disposed of after use. The chest strap comes in four different sizes (S, M, L, XL). The one-way electrodes are suited for short term measurements (1-2 days). For any measurement lasting more than 2 days, chest straps are highly recommended.
1. Using Consumer Devices
It’s tempting to opt for consumer-grade devices, especially when working with tight budgets. But these devices often don’t meet the standards required for accurate HRV measurement inresearch. They’re typically designed for everyday users rather than professionals, and they don’t provide access to raw data—making it difficult to ensure data accuracy.
How to Avoid This Mistake:
Stick with reputable, research-grade brands that specialize in providing raw data and meet the standards for scientific research. If you can’t access raw data or need to log into a portal to view results, you're likely dealing with a consumer-grade device. These devices aren’t suitable for high-quality, publishable research.
2. Using PPG in Ambulatory Measurements
Photoplethysmography (PPG) sensors can be useful for short-term, stationary measurements in a controlled environment. However, when it comes to real-world, ambulatory measurements, PPG can be prone to inaccuracies. It struggles to provide precise beat detection, which is essential for accurate HRV calculations. Movement artefacts and noise are common in real-world conditions.
How to Avoid This Mistake:
For more accurate HRV data, use an Electrocardiogram (ECG), which has a clear reference point (the R peak in the ECG signal) for detecting heartbeats. This method is far more reliable, especially in dynamic settings where a participant might be moving. Even research-grade PPG devices can struggle with accuracy in real-life situations, so ECG is generally a safer choice.
3. Using Devices That Only Record IBI or Have a Low Sampling Frequency
Not all ECG devices are equal! Some only record Inter-Beat Intervals (IBI), meaning you won’t have access to the raw signal data to check for artefacts. Additionally, devices that sample at low frequencies (under 1000Hz) compromise the accuracy and precision of HRV measurements.
How to Avoid This Mistake:
Ensure that the ECG device you’re using has a sampling frequency over 1000Hz and captures more than just IBIs. This way, you’ll have access to high-resolution data that allows you to view artefacts and ensure the integrity of your HRV measurements. Low-quality data can lead to skewed results, which undermines the value of your research.
4. Not Having Access to Raw Data
Raw data is essential for ensuring accurate HRV measurements. Without it, you cannot identify artefacts, noise, or anomalies in your data that could distort your findings. Without access to the raw ECG signal, you’re flying blind when it comes to interpreting HRV.
How to Avoid This Mistake:
Always ensure that your measurement devices provide access to raw data. If the device doesn’t allow you to view or download the raw signals, it’s not suitable for use in research. This step is crucial for identifying issues in the data that could impact the overall analysis and interpretation.
5. Using ECG in Isolation
Even with a high-quality ECG that records raw data at a high sampling rate, using it in isolation can lead to incomplete interpretations. HRV data, by itself, doesn’t provide the full context of what’s happening with the participant. Understanding how environmental or physical factors (such as movement, temperature, or barometric pressure) influence the data is essential for an accurate analysis.
How to Avoid This Mistake:
Incorporate additional signals like accelerometer, gyrometric, barometric, and temperature data alongside the ECG. These contextual data points help researchers understand the circumstances under which the HRV measurements occurred, giving more insight into how the participant's body responded to different situations. Context is crucial for accurate interpretation of HRV results.
It’s tempting to opt for consumer-grade devices, especially when working with tight budgets. But these devices often don’t meet the standards required for accurate HRV measurement inresearch. They’re typically designed for everyday users rather than professionals, and they don’t provide access to raw data—making it difficult to ensure data accuracy.
How to Avoid This Mistake:
Stick with reputable, research-grade brands that specialize in providing raw data and meet the standards for scientific research. If you can’t access raw data or need to log into a portal to view results, you're likely dealing with a consumer-grade device. These devices aren’t suitable for high-quality, publishable research.
2. Using PPG in Ambulatory Measurements
Photoplethysmography (PPG) sensors can be useful for short-term, stationary measurements in a controlled environment. However, when it comes to real-world, ambulatory measurements, PPG can be prone to inaccuracies. It struggles to provide precise beat detection, which is essential for accurate HRV calculations. Movement artefacts and noise are common in real-world conditions.
How to Avoid This Mistake:
For more accurate HRV data, use an Electrocardiogram (ECG), which has a clear reference point (the R peak in the ECG signal) for detecting heartbeats. This method is far more reliable, especially in dynamic settings where a participant might be moving. Even research-grade PPG devices can struggle with accuracy in real-life situations, so ECG is generally a safer choice.
3. Using Devices That Only Record IBI or Have a Low Sampling Frequency
Not all ECG devices are equal! Some only record Inter-Beat Intervals (IBI), meaning you won’t have access to the raw signal data to check for artefacts. Additionally, devices that sample at low frequencies (under 1000Hz) compromise the accuracy and precision of HRV measurements.
How to Avoid This Mistake:
Ensure that the ECG device you’re using has a sampling frequency over 1000Hz and captures more than just IBIs. This way, you’ll have access to high-resolution data that allows you to view artefacts and ensure the integrity of your HRV measurements. Low-quality data can lead to skewed results, which undermines the value of your research.
4. Not Having Access to Raw Data
Raw data is essential for ensuring accurate HRV measurements. Without it, you cannot identify artefacts, noise, or anomalies in your data that could distort your findings. Without access to the raw ECG signal, you’re flying blind when it comes to interpreting HRV.
How to Avoid This Mistake:
Always ensure that your measurement devices provide access to raw data. If the device doesn’t allow you to view or download the raw signals, it’s not suitable for use in research. This step is crucial for identifying issues in the data that could impact the overall analysis and interpretation.
5. Using ECG in Isolation
Even with a high-quality ECG that records raw data at a high sampling rate, using it in isolation can lead to incomplete interpretations. HRV data, by itself, doesn’t provide the full context of what’s happening with the participant. Understanding how environmental or physical factors (such as movement, temperature, or barometric pressure) influence the data is essential for an accurate analysis.
How to Avoid This Mistake:
Incorporate additional signals like accelerometer, gyrometric, barometric, and temperature data alongside the ECG. These contextual data points help researchers understand the circumstances under which the HRV measurements occurred, giving more insight into how the participant's body responded to different situations. Context is crucial for accurate interpretation of HRV results.
EDA and Activity Sensor EdaMove 4
The best locations to measure the electro-dermal activity are the inner surfaces of the hand and foot. If a measurement on the hands produces too many recording artefacts, then the feet are a viable alternative.
Analysis Software DataAnalyzer
Yes. Simply download the DataAnalyzer Software from our website. It comes with a 30 day free trial period, which can also be extended an additional 15 days upon request. Otherwise, to continue using the software you’ll need to purchase a licence.
The DataAnalyzer software is for a single-user license. When the program sends the request for a key, it is specific for the workstation that it is sent from. This means that a specific license key for each workstation on which the software will be used will be required. Once the software has been unlocked using a license key, it is registered exclusively for this workstation. If you need to use the DataAnalyzer on another computer, you will need to purchase an additional licence.
The software can be installed on computers running Microsoft Windows 7 and above.
If you need to use the DataAnalyzer software beyond the initial 30 day free trial, you need to register the product. A licence key must be purchased through movisens from the computer which you intend to use the software on. Once the licence is received from us, the software will be able to be used again.
The display of secondary parameters depends on what additional licence modules have been installed, and what sensor was utilised to gather the data. There are currently three additional modules available: EnergyExpenditure, Cardio, and EDA. The DataAnalyzer will recognise all of the measurement data and offer relevant secondary parameters. For example for a Cardio parameter the ECG signal is necessary. If the required signal isn’t available, the DataAnalyzer will not show the secondary parameter.
Currently the language of the software (English or German) is dependent on the language of the operating system.
You can find the version number at the top of the window after opening the software. To update the software, please use the updater which can be found via: Start Menu -> movisens DataAnalyzer -> Updater. The updates are free of charge.
The calculation of the AEE is based on acceleration data. From this data, everyday activities are recognised, and for each recognisable activity there is a model for the AEE calculation. This means that AEE cannot be calculated perfectly for non-everyday activities, especially activities with a static effort (ie without acceleration). In certain cases, the heart rate may be a better measure of stress. For example, before the actual investigation you could make measurements for everyday activities and then create an individual HR -> AEE model. Then during the actual examination, you can then use that data to convert HR values to AEE.
If the ECG Signal quality does not allow calculation, there are gaps in the representation of the HRV parameters. This inadequate signal quality can have different reasons:
- The belt is too tight or too loose.
- The belt has been placed in position too close to the start of the measurement. It takes about 10 minutes until the dry electrodes on the belt reach the optimum conductivity.
- Motion artefacts. Excessive movement or muscle strain at the electrode positions can lead to motion artefacts.
- Cardiac arrhythmia
- After every measurement we recommend checking the ECG data with the UnisensViewer. In doing so, one quickly develops a feeling on how to optimize the sensor for the generation of high-quality data.
SensorManager
This problem occurs when invalid entries are entered for the measurement duration. Prior to each measurement, adjustments are made to the duration of the measurement, in relation to the minutes, hours and days. The field for minutes allows values from 0 to 59. The field for hours allows values from 0 to 23. Examples: 24 hours -> 1 day; 60 minutes -> 1 hour; 119 minutes -> 1 hour, 59 minutes.
The data is saved in the unisens format by default. This format allows the data to be opened in the Unisens-Viewer. If the data is to be used in Excel, then during the save function, please select the “as .csv” option. We only recommend this option for short measurements.
movisensXS
This is the PIN for the study, which as default is set to 2486. The PIN can be configured in the “Study Running” Block.
We do not recommend the use of an account (i.e. e-mail address and password) by multiple users. However, each user can create an account using an e-mail address and invite other users. The inviting user (admin) can assign different read and write privileges for the new user. Each user can create and manage studies. The administrator does not have general view privileges, but he can still open the administration (https://xs.movisens.com/administration/users). Users can not access mutual studies, unless the administrator has granted appropriate rights.
In the entire XS environment, each user can only use one account (= e-mail address and password). It is thus not possible to be associated with different organizations with the same e-mail address. An e-mail address can be assigned to an organization. Please contact movisens if you want to change the organization.
The items are credited by movisens to an account (normally the account of the customer). Users who are members of the organization have the ability to use these credits. The administrator can control the consumption of the credits (https://xs.movisens.com/administration/billing). Occasionally fewer credits are used for a study than are available in the account. In this case, the credits are retained and can be used for another study. Contact us if you run out of credits during an ongoing study.