NIRS-EMG for Clinical Applications: A Systematic Review

Cerebral and muscle tissue oxygenation during exercise in healthy adults: A systematic review

BACKGROUND

Near-infrared spectroscopy (NIRS) technology has allowed for the measurement of cerebral and skeletal muscle oxygenation simultaneously during exercise. Since this technology has been growing and is now successfully used in laboratory and sports settings, this systematic review aimed to synthesize the evidence and enhance an integrative understanding of blood flow adjustments and oxygen (O2) changes (i.e., the balance between O2 delivery and O2 consumption) within the cerebral and muscle systems during exercise.

METHODS

A systematic review was conducted using PubMed, Embase, Scopus, and Web of Science databases to search for relevant studies that simultaneously investigated cerebral and muscle hemodynamic changes using the near-infrared spectroscopy system during exercise. This review considered manuscripts written in English and available before February 9, 2023. Each step of screening involved evaluation by 2 independent authors, with disagreements resolved by a third author. The Joanna Briggs Institute Critical Appraisal Checklist was used to assess the methodological quality of the studies.

RESULTS

Twenty studies were included, of which 80% had good methodological quality, and involved 290 young or middle-aged adults. Different types of exercises were used to assess cerebral and muscle hemodynamic changes, such as cycling (n = 11), treadmill (n = 1), knee extension (n = 5), isometric contraction of biceps brachii (n = 3), and duet swim routines (n = 1). The cerebral hemodynamics analysis was focused on the frontal cortex (n = 20), while in the muscle, the analysis involved vastus lateralis (n = 18), gastrocnemius (n = 3), biceps brachii (n = 5), deltoid (n = 1), and intercostal muscle (n = 1). Overall, muscle deoxygenation increases during exercise, reaching a plateau in voluntary exhaustion, while in the brain, oxyhemoglobin concentration increases with exercise intensity, reaching a plateau or declining at the exhaustion point.

CONCLUSION

Muscle and cerebral oxygenation respond differently to exercise, with muscle increasing O2 utilization and cerebral tissue increasing O2 delivery during exercise. However, at the exhaustion point, both muscle and cerebral oxygenation become compromised. This is characterized by a reduction in blood flow and a decrease in O2 extraction in the muscle, while in the brain, oxygenation reaches a plateau or decline, potentially resulting in motor failure during exercise.

Muscle specific declines in oxygen saturation during acute ambulation with hands-free and conventional mobility devices

Disuse is associated with reduced muscle oxygen saturation (SmO2). Improving oxygen delivery to tissues is important for healing, preventing muscle atrophy, and reducing the risk of deep vein thrombosis. Mobility devices are used during disuse periods to ambulate and protect the injured limb. This study examined SmO2 in walking and ambulation with various mobility devices. Thirty-eight participants randomly completed four, ten-minute trials which included: (1) walking, (2) medical kneeling scooter (MKS), (3) hands-free crutch (HFC), and (4) axillary crutch (AC). During each trial, near infrared spectroscopy sensors were placed on the vastus lateralis (VL), biceps femoris (BF), and lateral gastrocnemius (LG) of the right limb. Compared to walking, all mobility devices showed a decline in SmO2 in the VL of ∼10% (mean ± SD; 75% ± 12%-65% ± 17%, P < 0.05). In the BF, SmO2 declined ∼9% in AC compared to walking (76% ± 12%-67% ± 17%, P = 0.025). In the LG, SmO2 declined in AC (64% ± 16%) compared to MKS (70% ± 15%, P = 0.005). There were no differences in LG SmO2 compared to walking (69% ± 13%) in MKS (P > 0.05) or HFC (65% ± 15%, P > 0.05). In young, healthy volunteers, the use of mobility devices altered muscle oxygenation in several muscles. AC reduced muscle oxygenation in the VL, BF, and LG; while MKS and HFC maintained BF and LG muscle oxygenation at a level consistent with ambulatory walking.

A Wireless 2-Channel Layered EMG/NIRS Sensor System for Local Muscular Activity Evaluation

A wireless 2-channel layered sensor system that enables electromyography (EMG) and near-infrared spectroscopy (NIRS) measurements at two local positions was developed. The layered sensor consists of a thin silver electrode and a photosensor consisting of a photoemitting diode (LED) or photodiode (PD). The EMG and NIRS signals were simultaneously measured using a pair of electrodes and photosensors for the LED and PD, respectively. Two local muscular activities are presented in detail using layered sensors. In the experiments, EMG and NIRS signals were measured for isometric constant and ramp contractions at each forearm using layered sensors. The results showed that local muscle activity analysis is possible using simultaneous EMG and NIRS signals at each local position.

A Narrative Review on Multi-Domain Instrumental Approaches to Evaluate Neuromotor Function in Rehabilitation

In clinical scenarios, the use of biomedical sensors, devices and multi-parameter assessments is fundamental to provide a comprehensive portrait of patients' state, in order to adapt and personalize rehabilitation interventions and support clinical decision-making. However, there is a huge gap between the potential of the multidomain techniques available and the limited practical use that is made in the clinical scenario. This paper reviews the current state-of-the-art and provides insights into future directions of multi-domain instrumental approaches in the clinical assessment of patients involved in neuromotor rehabilitation. We also summarize the main achievements and challenges of using multi-domain approaches in the assessment of rehabilitation for various neurological disorders affecting motor functions. Our results showed that multi-domain approaches combine information and measurements from different tools and biological signals, such as kinematics, electromyography (EMG), electroencephalography (EEG), near-infrared spectroscopy (NIRS), and clinical scales, to provide a comprehensive and objective evaluation of patients' state and recovery. This multi-domain approach permits the progress of research in clinical and rehabilitative practice and the understanding of the pathophysiological changes occurring during and after rehabilitation. We discuss the potential benefits and limitations of multi-domain approaches for clinical decision-making, personalized therapy, and prognosis. We conclude by highlighting the need for more standardized methods, validation studies, and the integration of multi-domain approaches in clinical practice and research.

Multi-Sensing Techniques with Ultrasound for Musculoskeletal Assessment: A Review

The study of muscle contractions generated by the muscle-tendon unit (MTU) plays a critical role in medical diagnoses, monitoring, rehabilitation, and functional assessments, including the potential for movement prediction modeling used for prosthetic control. Over the last decade, the use of combined traditional techniques to quantify information about the muscle condition that is correlated to neuromuscular electrical activation and the generation of muscle force and vibration has grown. The purpose of this review is to guide the reader to relevant works in different applications of ultrasound imaging in combination with other techniques for the characterization of biological signals. Several research groups have been using multi-sensing systems to carry out specific studies in the health area. We can divide these studies into two categories: human-machine interface (HMI), in which sensors are used to capture critical information to control computerized prostheses and/or robotic actuators, and physiological study, where sensors are used to investigate a hypothesis and/or a clinical diagnosis. In addition, the relevance, challenges, and expectations for future work are discussed.

Wearable super-resolution muscle-machine interfacing

Muscles are the actuators of all human actions, from daily work and life to communication and expression of emotions. Myography records the signals from muscle activities as an interface between machine hardware and human wetware, granting direct and natural control of our electronic peripherals. Regardless of the significant progression as of late, the conventional myographic sensors are still incapable of achieving the desired high-resolution and non-invasive recording. This paper presents a critical review of state-of-the-art wearable sensing technologies that measure deeper muscle activity with high spatial resolution, so-called super-resolution. This paper classifies these myographic sensors according to the different signal types (i.e., biomechanical, biochemical, and bioelectrical) they record during measuring muscle activity. By describing the characteristics and current developments with advantages and limitations of each myographic sensor, their capabilities are investigated as a super-resolution myography technique, including: (i) non-invasive and high-density designs of the sensing units and their vulnerability to interferences, (ii) limit-of-detection to register the activity of deep muscles. Finally, this paper concludes with new opportunities in this fast-growing super-resolution myography field and proposes promising future research directions. These advances will enable next-generation muscle-machine interfaces to meet the practical design needs in real-life for healthcare technologies, assistive/rehabilitation robotics, and human augmentation with extended reality.

A Systematic Review of Sensor Fusion Methods Using Peripheral Bio-Signals for Human Intention Decoding

Humans learn about the environment by interacting with it. With an increasing use of computer and virtual applications as well as robotic and prosthetic devices, there is a need for intuitive interfaces that allow the user to have an embodied interaction with the devices they are controlling. Muscle-machine interfaces can provide an intuitive solution by decoding human intentions utilizing myoelectric activations. There are several different methods that can be utilized to develop MuMIs, such as electromyography, ultrasonography, mechanomyography, and near-infrared spectroscopy. In this paper, we analyze the advantages and disadvantages of different myography methods by reviewing myography fusion methods. In a systematic review following the PRISMA guidelines, we identify and analyze studies that employ the fusion of different sensors and myography techniques, while also considering interface wearability. We also explore the properties of different fusion techniques in decoding user intentions. The fusion of electromyography, ultrasonography, mechanomyography, and near-infrared spectroscopy as well as other sensing such as inertial measurement units and optical sensing methods has been of continuous interest over the last decade with the main focus decoding the user intention for the upper limb. From the systematic review, it can be concluded that the fusion of two or more myography methods leads to a better performance for the decoding of a user's intention. Furthermore, promising sensor fusion techniques for different applications were also identified based on the existing literature.

Research and application advances in rehabilitation assessment of stroke

Stroke has a high incidence and disability rate, and rehabilitation is an effective means to reduce the disability rate of patients. To systematize rehabilitation assessment, which is the foundation for rehabilitation therapy, we summarize the assessment methods commonly used in research and clinical applications, including the various types of stroke rehabilitation scales and their applicability, and related biomedical detection technologies, including surface electromyography (sEMG), motion analysis systems, transcranial magnetic stimulation (TMS), magnetic resonance imaging (MRI), and combinations of different techniques. We also introduce some assessment techniques that are still in the experimental phase, such as the prospective application of artificial intelligence (AI) with optical correlation tomography (OCT) in stroke rehabilitation. This review provides a useful bibliography for the assessment of not only the severity of stroke injury, but also the therapeutic effects of stroke rehabilitation, and establishes a solid base for the future development of stroke rehabilitation skills.

Gesture Recognition Using Surface Electromyography and Deep Learning for Prostheses Hand: State-of-the-Art, Challenges, and Future

Amputation of the upper limb brings heavy burden to amputees, reduces their quality of life, and limits their performance in activities of daily life. The realization of natural control for prosthetic hands is crucial to improving the quality of life of amputees. Surface electromyography (sEMG) signal is one of the most widely used biological signals for the prediction of upper limb motor intention, which is an essential element of the control systems of prosthetic hands. The conversion of sEMG signals into effective control signals often requires a lot of computational power and complex process. Existing commercial prosthetic hands can only provide natural control for very few active degrees of freedom. Deep learning (DL) has performed surprisingly well in the development of intelligent systems in recent years. The significant improvement of hardware equipment and the continuous emergence of large data sets of sEMG have also boosted the DL research in sEMG signal processing. DL can effectively improve the accuracy of sEMG pattern recognition and reduce the influence of interference factors. This paper analyzes the applicability and efficiency of DL in sEMG-based gesture recognition and reviews the key techniques of DL-based sEMG pattern recognition for the prosthetic hand, including signal acquisition, signal preprocessing, feature extraction, classification of patterns, post-processing, and performance evaluation. Finally, the current challenges and future prospects in clinical application of these techniques are outlined and discussed.

Sustained fatigue assessment during isometric exercises with time-domain near infrared spectroscopy and surface electromyography signals

The effect of sustained fatigue during an upper limb isometric exercise is presented to investigate a group of healthy subjects with simultaneous time-domain (TD) NIRS and surface electromyography (sEMG) recordings on the deltoid lateralis muscle. The aim of the work was to understand which TD-NIRS parameters can be used as descriptors for sustained muscular fatigue, focusing on the slow phase of this process and using median frequency (MF) computed from sEMG as gold standard measure. It was found that oxygen saturation and deoxy-hemoglobin are slightly better descriptors of sustained fatigue, than oxy-hemoglobin, since they showed a higher correlation with MF, while total-hemoglobin correlation with MF was lower.

Validation of Fabric-Based Thigh-Wearable EMG Sensors and Oximetry for Monitoring Quadriceps Activity during Strength and Endurance Exercises

Muscle oximetry based on near-infrared spectroscopy (NIRS) and electromyography (EMG) techniques in adherent clothing might be used to monitor the muscular activity of selected muscle groups while exercising. The fusion of these wearable technologies in sporting garments can allow the objective assessment of the quality and the quantity of the muscle activity as well as the continuous monitoring of exercise programs. Several prototypes integrating EMG and NIRS have been developed previously; however, most devices presented the limitations of not measuring regional muscle oxyhemoglobin saturation and did not embed textile sensors for EMG. The purpose of this study was to compare regional muscle oxyhemoglobin saturation and surface EMG data, measured under resting and dynamic conditions (treadmill run and strength exercises) by a recently developed wearable integrated quadriceps muscle oximetry/EMG system adopting smart textiles for EMG, with those obtained by using two "gold standard" commercial instrumentations for EMG and muscle oximetry. The validity and agreement between the wearable integrated muscle oximetry/EMG system and the "gold standard" instrumentations were assessed by using the Bland-Altman agreement plots to determine the bias. The results support the validity of the data provided by the wearable electronic garment developed purposely for the quadriceps muscle group and suggest the potential of using such device to measure strength and endurance exercises in vivo in various populations.

Time-Gated Single-Photon Detection in Time-Domain Diffuse Optics: A Review

This work reviews physical concepts, technologies and applications of time-domain diffuse optics based on time-gated single-photon detection. This particular photon detection strategy is of the utmost importance in the diffuse optics field as it unleashes the full power of the time-domain approach by maximizing performances in terms of contrast produced by a localized perturbation inside the scattering medium, signal-to-noise ratio, measurement time and dynamic range, penetration depth and spatial resolution. The review covers 15 years of theoretical studies, technological progresses, proof of concepts and design of laboratory systems based on time-gated single-photon detection with also few hints on other fields where the time-gated detection strategy produced and will produce further impact.