About this Research Topic
The human brain constantly receives external environmental inputs, creates complex thoughts and memories, initiates body movements, and adapts itself over time as we live our experiences. Traditional experiments have stayed in a controlled laboratory environment and examined simplified tasks and cues, with minimized distractions and stimuli, which remains the state-of-the-art approach to human neuroscience studies. In recent years, various modalities of wearable sensing technologies have become more ubiquitous, including motion sensors, neurophysiological sensors, as well as advanced algorithms to process and understand real-world data. Such emerging technologies have the potential to transform human neuroscience studies by examining human brain processes in a natural, out-of-the-laboratory setting to advance our understanding of the intricate interplay of intrinsic and extrinsic factors that contribute to brain function and health.
While wearable technologies are enabling out-of-laboratory human neuroscience data collection, there are still several major factors limiting their utility in research. First, many wearable technologies have insufficient validation and development for real-world data collection. Second, out-of-laboratory data are inherently noisy. As such, hardware and software methods are required to identify and/or reduce noise, such that data can be interpreted in a meaningful way. Third, the interpretation of data requires novel algorithms that may not be the same as those applied for traditionally controlled laboratory experiments. As a result, more research is required for technology validation, noise mitigation, and data interpretation.
The goal of the current research topic is to address this research need to improve the readiness of wearable technologies for out-of-laboratory human neuroscience research. The current research topic encompasses the design and validation of wearable technology for human neuroscience research as well as the demonstration of novel applications of wearable technologies in providing insight into human brain function/health in real-world settings.
While wearable technologies are enabling out-of-laboratory human neuroscience data collection, there are still several major factors limiting their utility in research. First, many wearable technologies have insufficient validation and development for real-world data collection. Second, out-of-laboratory data are inherently noisy. As such, hardware and software methods are required to identify and/or reduce noise, such that data can be interpreted in a meaningful way. Third, the interpretation of data requires novel algorithms that may not be the same as those applied for traditionally controlled laboratory experiments. As a result, more research is required for technology validation, noise mitigation, and data interpretation.
The goal of the current research topic is to address this research need to improve the readiness of wearable technologies for out-of-laboratory human neuroscience research. The current research topic encompasses the design and validation of wearable technology for human neuroscience research as well as the demonstration of novel applications of wearable technologies in providing insight into human brain function/health in real-world settings.
Keywords: out-of-laboratory studies, wearable sensors, sensor validation
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