By 2025, there will be approximately 463 exabytes of new data created each day across the internet-a number truly unimaginable. This data comes from commonplace items like ~300 billion emails or ~95 million shared photos. These items are openly shared intended to be viewed. However, most of this daily data deluge comes from less known, more mundane subsurface items like metadata, location data, interaction logs, archived browsing history, and more. While seemingly uninteresting, it turns out that when collected and analyzed in bulk, over time, it can be amazingly accurate at predicting human states, i.e:
- Healthy vs. sick.
- General activities.
- Sleeping vs. exercising.
- Future behavior like potential purchases or election votes.
As neuroscientists, we can leverage this data to learn more about the human mind. After all, elucidating factors at the foundation of human activity and/or behavior is at the core of neuroscience research. This article provides seven ways remote data collection is improving neuroscience research.
Neuroscientists have been using remote data collection techniques for decades. What has changed in recent years is:
- Just how distant “remote” can truly be.
- The number of subjects that can participate.
- The type of endpoints that can be measured and processed in a single experiment.
Research isn’t the only application for remote data collection and application. Recent advancements in Virtual Reality (VR) systems have brought the laboratory into virtual spaces. For example, medically, these advancements in VR systems for neuroscience research allow easier access to performing remote surgeries around the globe. In this scenario, the VR headset stays with the operating team so that when the surgeon arrives, he can see the quality of the near-real-time video feed coming from the patient hundreds of miles away.
In minor situations, the use of video alone would suffice, but with this augmented reality, they pair video with haptic feedback in both live surgery and educational/training surgical assignments. You could say this is similar to a rumble strip on game control but far more advanced.
As highlighted below, there are several reasons (well, at least seven) why a medical process, researcher or neuro-marketer would choose to use modern technology to collect, process, and analyze global, remotely-collected data.
1. The Comfort and Ease of Home
Stressed subjects make for stressed data.
It is well recognized that exposure to stressful factors before performing a behavioral test may modify the subsequent data collected. Moreover, it has been repeatedly demonstrated that, in addition to acute effects, environmental stressors can result in long-term effects. Scientists’ best hope is to mitigate such external variables while accepting that they can never be entirely eliminated. As such, if each of the subjects is treated identically, they are equally exposed to all elements.
A Human Being Tested in Their Own Home
Driving to a doctor’s office, worrying about costs, a diagnosis, finding the right office, or if you are parked legally are all very real stressors. However, suppose research data collection could be done to avoid these external factors, like in the comfort of one’s own home. In that case, the impact of stressful travel would not overshadow the study’s focus.
That said, it is not possible to completely isolate or eliminate the effects of external forces on research subjects. The best approach to minimize stressors is to expose all subjects to the same circumstances using innovative but validated equipment.
2. Force majeure
When unforeseen disaster strikes, you must adapt your behavior. Enter, COVID-19.
The last three years have been eye-opening across the board due to the global COVID-19 pandemic. Sometimes there are just extraordinary events or circumstances beyond the control of the researchers. These unforeseen circumstances force adaptation to new constraints.
Determining the most effective advertising campaign using the best technology available is a no-brainer to capitalists. However, the fact is: a subject’s data quality is not dependent on their proximity to the researcher. Therefore, the researcher’s core job of collecting data from subjects should adapt to the tools currently available.
3. EverlyWell, Apple Watch & Telesurgery
EverlyWell is a mail-order medical laboratory testing service that ships pre-packaged kits with easily understood instructions to quantify targets across over 30 diagnostic tests. The Apple Watch has also made headlines for its heartbeat abnormality notification and fall detection. For both EverlyWell and Apple, there has been very little doubt in their products’ ability to add value for less travel and costs for the consumer market.
With products like those and others, we, as a society, seem to have already accepted and trusted biomedical data collected locally, processed remotely, and presented properly. Whether it is for disease prevention, mental wellness, attacking sickness or maintaining a well-balanced body, you want to get feedback and hopefully be rewarded when health goals are accomplished. In the dark days before the internet, when computers took up an entire room, measuring and tracking your fitness Key Performance Indicators (KPI) was a totally analog endeavor. This is no longer the situation. As a result, the “quantified self” movement rapidly maturing.
Most commonly monitored KPIs include:
- Heart rate
- Blood pressure
- Sleep duration
- Movement patterns
All of which can be quantified easily with the proper sensor and basic hardware. It is common knowledge that neuroscience and many biomedical disciplines have sample size problems. In trying to solve this problem, the best approach would be to add additional subjects rather than train the smaller group of subjects selected because they are in close proximity. With the full range of remote KPIs measurable, this is a viable way for neuroscience research to thrive and survive.
4. Increasing Inclusion and Diversity of Participants
Who is the WEIRD group, and why do we know so much about them in particular?
“Behavioral scientists routinely publish broad claims about human psychology and behavior in the world’s top journals based on samples drawn entirely from Western, Educated, Industrialized, Rich, and Democratic (WEIRD) societies.”
It’s a common trope that psychology knows a lot about college-age, white, affluent individuals but very little about humans in general.
Psychology experiments are performed on college campuses, and subject inclusion criteria are not much broader than their proximity and availability during the day. To make conclusions about the broader population, sample groups for psychology experiments need to include more individuals from diverse backgrounds. The key to this problem lies in remote data collection equipment, especially equipment designed for the consumers to use themselves.
5. Short-term and Long-term Cost Reductions
Modern cloud platforms have made the physical distance irrelevant.
Using a remote data collection tool saves money on advertisements.
Randomized samples cost more than convenience samples, e.g., college students, because you need to advertise for the research subjects in the local community. Simply put, advertising costs money.
Using a remote data collection tool saves money on proprietary IT and neuro-analysis equipment.
Often, individual research laboratories have to pay for and maintain their own IT equipment, especially if it is specialized hardware for data collection. Of course, as time goes on, technology improves. In the meantime, updating infrastructure is a high cost. For this reason, access to modern cloud platforms and reduced-cost data collection hardware can lessen resource use in neuroscience research.
6. Quantifying Physiology and Behavior has always been “remote”
The distance between the sensor hardware and data processing software is irrelevant.
Understanding, predicting, and healing human behavior is at the core of most academic research, especially neuroscience. Typically, the notion of “behavioral data collection” conjures images of scientists in suspiciously unstained lab jackets watching subjects afar with a clipboard and stopwatch while scribbling every now and then.
This is a simple idea, but it is riddled with potential sources of unknown variance that could influence a subject’s activity or behavior. In scientific experiments, the goal is to eliminate as much of this unaccounted variance as possible. This practice is essential to make evidence-based conclusions about the cause when an effect is observed.
How to Remove Sources of Error in Neuroscience Research
The quest to remove sources of error when quantifying human physiology and behavior is ongoing. At its most basic, this typically involves improvements to hardware that collect data from sensors, which is then processed using analog or digital software to identify items of interest, trends, or differences between or within-subjects. Remote Data Collection is more powerful than initially assumed and can provide diverse but relevant data sets that add predictive power to the experiment.
7. Machine Learning Offers Better Data
Data + Metadata + Machine Learning (ML) = most comprehensive model of behavioral activity.
Artificial intelligence models of who you are, where you are, what you love and hate, are all being used at a scale many are unaware of. Fortunately, there are commercial neuroscience data collection equipment available in our modern-day market. Their use of data and advertisement metadata will likely result in a more comprehensive understanding of behavior than what could be collected in more sterile, isolated laboratory settings.
At its core, provided data (name, location, birthday) is merged with subsurface metadata (time on site, previous site, exit site) and has unleashed completely new analysis techniques that turn out to be extremely useful for measuring and predicting human behavior.
Would You Like to Learn More? Meet EMOTIV
In highlighting the techniques above, we have demonstrated that remote data collection is not new and continues to improve neuroscience research as technology improvements hit the market. Given the rate at which “remote” expanded from across the hall, to down the block, to across the country and now, around the world, it is easy to understand feelings of uneasiness felt by traditional researchers. However, considering the magnitude of technical improvements to consumer hardware and monumental achievements in cloud-based data analysis and processing, the term “remote” quickly becomes irrelevant to how data is collected.
In summary, subjects can perform data collection at home without the direct oversight of the research staff. They can collect this information about their brain for personal use but also have the option to upload their EEG or collect EEG specifically for more extensive, ongoing research projects.
Founded in 2011, EMOTIV is a San Francisco-based bioinformatics company with a mission of advancing our understanding of the human brain using custom electroencephalography (EEG) hardware, analysis, and visualization. EMOTIV’s approach to EEG research more closely reflects “real-world” conditions, as individuals being tested are in locations and environments that are more reflective of how they actually live their lives.
EMOTIV serves a wide community of users, from professionals to individuals who seek, simply, to learn about their brains. The EMOTIV INSIGHT 5-channel EEG headset is designed for brain-computer interface (BCI). Insight combines a sleek easy-to-set-up design with revolutionary sensor technology.
EMOTIV EPOC X and EPOC Flex
The EMOTIV EPOC X and EPOC Flex offer a 14-channel & 32-channel EEG system. Designed for neuroscience research in every setting, the EPOC headsets are wireless with improved sensor technology. Both headsets have been validated by independent research groups and are proven to provide high-quality research-grade data.
A complete comparison of the technical capabilities of EMOTIV’s EEG systems is available for review.
We have a suite of tools to support every step of neuroscience research along the way.
EmotivPRO software allows users to process, analyze and visualize trial results. Researchers can also design experiments at the professional level in which any participant with an EMOTIV headset can participate if compliant with the experimental design.
A Software Development Kit (SDK) for EMOTIV is also available so that custom apps, interactions, or experimental designs can be performed on the go using the headset and smartphone alone.
As the number of disciplines and commercial markets embracing neuroscience tools and methodologies increases, EMOTIV’s low-cost, ease-of-use EEG system(s) are being used in:
- Neuroscience research
- Health and wellness marketing initiatives
- Automotive industries
- Consumer research
- Entertainment settings
Additionally, with the quality, cost, and ability to ship EMOTIV headsets worldwide, researchers can recruit and enroll a diverse array of qualified participants. Due to the quality control metrics the processing software evaluates, researchers can also trust the data collection process.