Tag: fNIR

VR Integration: Enhancing Research with Virtual Environments

Measuring the human body and brain’s response to real-world conditions and stimuli has long challenged researchers. This problem has usually been dealt with in one of two ways. The first approach is to take research participants into the field—not impossible with today’s mobile data recording technology but not always safe or convenient. The second option is to imitate real-world conditions in the lab using screens, audio equipment, and even scent delivery, but in the end, it is difficult to completely remove the lab setting from the participant’s experience—that is, until the introduction of Virtual Reality (VR) technology in research.

Just as it has revolutionized everything from entertainment to training, VR has provided researchers with the opportunity to create immersive experiences in the lab that mimic the real world. Advances in technology have not only made these simulated environments more realistic, but they have also made it easier to integrate a wide range of signals and stimulus delivery to enhance the recording of physiological and psychophysiological data.

BIOPAC, through cooperation with several partner companies, offers a range of data recording options that integrate seamlessly with third-party VR devices. fNIR Devices, for example, designs solutions for recording functional near-infrared spectroscopy (fNIRS) signals that can easily be incorporated with standard VR head-mounted displays (HMD) to measure neural activity and hemodynamic response in the prefrontal cortex while participants experience VR environments. BIOPAC partner Seenel has created MedelOpt, a line of whole-head wearable devices that combine electroencephalography (EEG) and fNIRS, including a VR option that integrates an HMD. Finally, partner company WorldViz offers a full spectrum of VR solutions from complete VR kits to full-room Projection VR technology to software that can be combined with both wired and wireless data recording technologies to provide a complete array of bio-signal data, from eye tracking to electrodermal activity.

A Canadian study published in 2023 used a combination of BIOPAC and WorldViz products to investigate how sensory feedback and arousal influence neuromusVR Shadowcular control and posture. Researchers measured arousal via electrodermal activity (EDA) and psychosocial questionnaires, rating perceived fear and anxiety in both real-world situations in VR environments that simulated standing both at ground level and on a raised platform. Participants wore a commercial HMD running WorldViz’s Vizard VR toolkit software. Electrical nerve stimulation was provided via a BIOPAC linear isolated stimulator. The study found the “physiological and perceptual indicators of fear and anxiety increased” in the VR platform simulation, providing “novel evidence that VR can be used to modulate upright postural control.”

A similar study published in the 2022 issue of the Journal of Sport Rehabilitation examined the effect non-physical mental training has on balance skills. The study used fNIRS technology to measure hemodynamic response in the prefrontal cortex of participants experiencing virtual environments through VR HMDs. Participants were instructed to imagine themselves imitating balance exercises viewed through an Oculus VR HMD while also fitted with an fNIR Devices Imager headband. Data was gathered using Cobi Studio software and analyzed via fNIRSoft software. The study identified several advantages of virtual reality mental training (VRMT) over conventional mental training (CMT).

These are just a few examples of how VR technology can be integrated with a variety of methodologies for gathering research data. For additional information on the subject, check out our Virtual Reality Resources, which include an array of online training on integrating VR into research.

Are you planning a research product and need help integrating VR with other data acquisition and analysis equipment? Contact your local BIOPAC sales rep to find the right solutions for you.

Dark Current Measurement as a Noise Management Tool

Noise in functional near infrared (FNIR) imaging data utilized for neurophysiological brain functioning research is a challenge to researchers, The use of dark current measurement in functional near infrared (fNIR) brain imaging can provide a valuable tool in identifying and managing certain type of noise in recordings.

By Davood Tashayyod, FNIR Devices

The use of dark current measurement in functional near infrared (fNIR) brain imaging (measurements taken not only when LED type light sources shine light at wavelengths 730 and 850 nm but also when they do not shine light (dark current condition)) can provide a valuable tool in identifying and managing certain types of noise in recordings.

Noise in functional near infrared (fNIR) imaging data utilized for neurophysiological brain functioning research is a challenge to researchers, in that excessive or unmanaged noise may pose a risk to the quality of gathered data and hence in the interpretation of the results. This noise arises from two general categories of sources, biological sources and non-biological sources. It should be noted that sources of noise are routinely present, so that noise cannot be eliminated but rather must be managed. Biological sources of noise include the respiratory and cardiac cycles and slow vasomotor oscillations. Non-biological sources of noise may include contamination from other external devices and noise induced by improper sensor application (light leakage, in the case of fNIR sensors), cable movements, or instruments or equipment used in the course of the experiment. These sources, independently or in combination, can mask the signals of interest.

Close attention to good laboratory practices, to include proper sensor placement, trial runs to establish baselines, and other techniques can help to reduce noise. Close attention to experiment protocols during the experiment can also be of assistance. However, it is in post-experiment data processing and analysis phases that the researcher has the greatest number of tools to manage noise. These tools include intuitive or visual analysis, filtering, and specialized analysis. Each method has strengths and weaknesses, but used in combination they offer a reliable method of managing noise and improving data quality.

Visual or intuitive analysis depends upon researcher experience and qualification, and some artifacts may be too small to be readily apparent. Filtering is useful, but in some range of measurements noisy data segments may be so great or may not contain any signal originated from the brain such as in the case when the sensor loses contact with the skin and captures data only from the ambient that it may not make sense to remove noise, rather such data segments should be identified and discarded.

Specialized analysis, such as dark current measurement, provide a very useful method for both identifying the noise not readily apparent to the naked eye and identifying data segments where filtering is likely to not be useful. A discussion of the use of dark current measurement can be found here.

For more information on optical braining imaging systems, visit BIOPAC’s fNIR page. BIOPAC also provides a wide range of tools for recording, displaying, classifying, and analyzing psychophysiological measurements—including EEG, ECG, EDA, PPG, and emotional states—visit BIOPAC’sapplications pages and view BIOPAC’s full line of physiology data acquisition and analysis systems, electrodes,amplifiers, and wearable, wireless transmitters and loggers.

BIOPAC Systems, Inc. provides life science researchers and educators with data acquisition and analysis systems that inspire people and enable greater discovery about life. Visit us at www.biopac.com.

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