Portable fNIRS in Sports: Measuring Brain Function in Real-World Settings

Introduction

Understanding how the brain functions during sport and exercise is critical for optimizing athletic performance, preventing injury, and supporting recovery. This is especially relevant in collision and high-impact sports, where concussions and other forms of traumatic brain injury (TBI) are relatively common, yet often difficult to detect in real time. As McCrory et al. (2017) emphasize, sport-related concussion represents “a traumatic brain injury induced by biomechanical forces, ” but timely and accurate detection during play remains a major challenge.

Current real-time assessments typically rely on computerized cognitive tools like ImPACT, which offer objective reaction time and memory measures; however, these tools may yield inconsistent results in subacute or chronic phases and should not be used in isolation for return-to-play decisions (Powell et al., 2021). Portable neuroimaging technologies, such as wearables and head impact sensors, are increasingly being explored to detect subtle functional and structural brain changes immediately after impacts, offering more sensitive and direct indicators of injury status (Zhan et al., 2020).

Traditional neuroimaging methods such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) have significantly advanced our understanding of brain function. However, applying these techniques in sporting contexts poses practical challenges. fMRI offers excellent spatial resolution but requires participants to remain entirely still and can only be used in laboratory settings, making it unsuitable for use during or immediately after physical activity. While EEG offers greater mobility and excellent temporal resolution, it provides poor spatial accuracy and remains highly susceptible to motion artifacts—a factor well-documented in mobile brain imaging research (Gramann et al., 2014).

Functional near-infrared spectroscopy (fNIRS) is an emerging neuroimaging technique that addresses many of the limitations of traditional methods. fNIRS works by emitting near-infrared light onto the scalp and skull to measure changes in oxygenated (HbO) and deoxygenated hemoglobin (HbR) in the cortical surface. These hemodynamic changes reflect underlying neural activity, enabling researchers to infer brain function with reasonable spatial and temporal resolution in more naturalistic settings compared to fMRI and EEG (Ferrari & Quaresima, 2012).

This paper evaluates whether portable fNIRS holds significant promise as a neuroimaging tool for examining brain function in real-world sporting settings. First, it addresses the limitations of conventional methods such as fMRI and EEG in athletic contexts. Next, the mechanisms of fNIRS are explained, emphasizing features that make it particularly well-suited for use during or immediately after physical activity—namely, its portability, non-ionizing nature, and resilience in mobile, dynamic environments (Rahimpour Jounghani et al., 2025; Scholkmann et al., 2014). Following this, the review explores emerging sports neuroscience applications of fNIRS, including its use in assessing motor control, monitoring cognitive workload and fatigue, and informing concussion management. The paper concludes by discussing key challenges and feasibility concerns surrounding its implementation, as well as future directions for integrating fNIRS into sports research and practice. Taken together, this analysis demonstrates how fNIRS can contribute valuable insights into athletic performance, injury prevention, and recovery strategies.

Overview of Neuroimaging Methods

Neuroimaging techniques such as fMRI, EEG, and PET have each contributed valuable insights into brain function. However, they face substantial limitations when applied to athletic and physically active contexts.

fMRI measures blood-oxygen-level–dependent (BOLD) signals and offers excellent spatial resolution (Logothetis, 2008), but it requires complete stillness in a controlled laboratory environment. This makes it unsuitable for capturing brain activity during or immediately following physical exertion. EEG, by contrast, is portable and capable of recording rapid neural responses with high temporal precision. Yet, it suffers from low spatial resolution and is highly sensitive to motion artifacts, limiting its utility in dynamic, real-world environments (Gramann et al., 2014). PET is useful for investigating long-term brain function through metabolic and neurotransmitter activity (Villringer & Dirnagl, 1995), but its reliance on radioactive tracers renders it invasive and impractical for use with athletes (Huang, 2000).

Taken together, these limitations highlight the need for a neuroimaging technique that is portable, non-invasive, and robust against movement—something that can deliver reliable insights into brain function directly in field or sporting environments.

Functional Near-Infrared Spectroscopy (fNIRS)

Because of its motion tolerance and portability, fNIRS has special promise for the study of sport. Oxygenated as well as deoxygenated hemoglobin may be detected to enable fNIRS to provide information regarding brain activity. These changes reflect neural activity caused by neurovascular coupling, in much the same manner as the blood-oxygen-level-dependent (BOLD) signal in fMRI (Ferrari & Quaresima, 2012). For example, Yu et al. (2023) found that athletes who were allowed to remain in play showed more vigorous hyperactivation while performing a visual attention task than athletes who were taken out immediately, the suggestion being that remaining on the field following injury will alter patterns of brain activity visible through fNIRS — patterns otherwise missed in traditional sideline testing.

fNIRS is particularly well suited to study athletes under natural sport environments and has many advantages. First, with its wearable and mobile configuration, fNIRS can be utilized to gather data when an athlete is training, sideline testing, or for other field-based studies (Pinti et al., 2015). Secondly, because of its accommodation to moderate levels of physical activity, it is far more practical to use than fMRI or EEG in dynamic settings. Third, as it provides acceptable spatial and temporal resolution, it permits both transient instability of brain activity and trends over extended periods spanning many sessions to be tracked. For example, a systematic review of 29 exercise studies demonstrated that regular exercise increases oxygenated hemoglobin in both the prefrontal and motor cortices. This increase is related to improved working memory and inhibitory control. Besides, the method is motion-robust, making it suitable to be used in real sporting settings (Shen et al., 2024). By avoiding tracer injection or exposure to high magnetic fields, this non-invasive method poses little safety concerns for athletes compared to imaging techniques such as PET or fMRI involving radiation or high-field magnet exposure. Lastly, scientists can observe neurovascular coupling directly, relate physical effort, mental demand, and brain function by measuring oxygenated and deoxygenated hemoglobin — a method that can be applied to optimize performance as well as avert damage (Gramann et al., 2014).

Potential Applications in Sports

Monitoring cognitive load during training and competition – By measuring prefrontal cortex activation, fNIRS can help assess how mental demands fluctuate during complex plays, multitasking, or high-pressure decision-making (Herff et al., 2014).

Studying focus, attention, and decision-making – Because fNIRS is able to capture changes in cortical activity, it can help find neural markers of optimal focus, allowing coaches to tailor drills and game strategies accordingly in practice to maximize focus. This includes revealing how athletes with different skill levels allocate attention and process information during sport tasks. For example, juggling and table tennis athletes showed much larger increases in oxygenated hemoglobin compared to novices within motor-related cortical regions (e.g., M1, premotor cortex, inferior parietal cortex). This indicates that an important reason for efficient integration of motor control and decision-making processes is a higher skill level (Perrey, 2008).

Evaluating fatigue – By tracking brain activity during states of physical and mental fatigue, fNIRS can detect alterations in brain function that correlate with slower reactions, impaired decisions, and heightened injury risk. This is significant because Van Cutsem et al. (2017) showed that subsequent disturbances in balance, motor skills, and decision-making processes could potentially increase the vulnerability to injury – meaning that alterations in the brain that can be measured by fNIRS can directly cause detectable decreases in function that make the individual more likely to be involved in an accident.

Supporting safer return-to-play decisions after concussion – Taylor (2021) showed that fNIRS is a valid tool when assessing concussion in athletes undergoing return-to-play protocols, showing that it can provide objective physiological confirmation of recovery — an advantage over relying solely on symptom reports, which can be incomplete or inaccurate.

Integration with other wearable technologies – Linking fNIRS data with other information from heart rate monitors, GPS trackers, and motion sensors enhances the ability to assess athlete performance and workload in depth (Pinti et al., 2020).

Challenges and Limitations

Despite its promise, fNIRS is not without limitations. Firstly, it is less suitable for investigating deep brain structures involved in sports performance because its measurement depth is restricted to only the outer cortical layers (Ferrari & Quaresima, 2012). Additionally, other factors can interfere with signal quality, such as hair density and color, as can ambient light in certain environments (Scholkmann et al., 2014). Because data analysis requires specialized expertise, unqualified analysis can lead to improper handling and eventually improper interpretations (Boas, Elwell, Ferrari, & Taga, 2014). There are also ethical considerations: brain data is inherently sensitive, and its collection raises privacy concerns, especially when linked to athletic performance and health outcomes (Ienca & Andorno, 2017). Before implementing fNIRS, informed consent and data governance protocols are essential in sports contexts and really, any context.

Future Directions

Technological developments could greatly expand the utility of fNIRS in sports. Developments that are current are making headsets lighter, more ergonomic, with greater sensor sensitivity and stronger motion artifact resistance, a very critical constraint for fNIRS (Yücel et al., 2021). For example, Spectroscopy Online (2024) reports that “a wireless, wearable brain-monitoring device using functional near-infrared spectroscopy (fNIRS) to detect cognitive fatigue in real time” already exists, which shows that such developments are not hypothetical but functional in real-world settings. Employing machine learning to analyze signals could streamline and enrich interpretation, lowering the expertise level required (Zhao et al., 2023). Athletes can also potentially be monitored over a season to identify trends in cognitive load, recovery, and injury risk, which can be referred to as large-scale monitoring. In combination with behavioral performance measures, biomechanical measures, and physiological monitoring, researchers would be able to provide individualized training plans and improve return-to-play decision safety (Perrey et al., 2024).

Conclusion

fNIRS holds strong promise for advancing the field of sports neuroscience. Its portability and ability to measure cortical activity in real-world settings provide a unique advantage over traditional imaging tools. By enabling researchers and clinicians to assess cognitive load, fatigue, focus, and recovery in naturalistic environments, fNIRS has the potential to directly improve both athlete performance and safety. At the same time, the successful integration of fNIRS into sports research and practice will require continued progress in device technology, data analysis methods, and ethical safeguards to protect athletes’ privacy. While challenges remain, the growing body of evidence demonstrates that fNIRS can bridge the gap between laboratory neuroscience and applied sports performance, making it a powerful tool for the next generation of athlete monitoring and individualized training.

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