A portable wireless near-infrared spatially resolved spectroscopy system for use on brain and muscle

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 Flexible Optoelectronic Device for Continuous Cerebral Blood Flow Monitoring

Human cerebral oxygenation and hemodynamics can be estimated by cerebral oxygenation parameters. Functional near-infrared spectroscopy (fNIRS) can be used to measure the hemoglobin concentration index of brain tissue noninvasively and in real time. However, limited by cumbersome equipment, high price and uncomfortable wear, conventional fNIRS monitoring systems still cannot achieve continuous and long-term monitoring. In this work, a flexible and wearable long-term monitoring system is developed featured with cost efficiency, simple preparation and light weight (only 1.6 g), which consists of a pair of light-emitting diodes (LEDs) and a photodetector (PD). Triangular serpentine interconnectors are introduced to connect the functional elements, enabling the device to be stretched in multiple directions. The device can continuously work for 7 h and be subjected to 2000 cycles of bending loading, with less than 3% change in voltage value, 1.89% and 1.9% change in LED luminous power and 0.9% change in voltage value. Furthermore, the hand-gripping and breath-holding experiments show that the system can accurately measure the changes in hemoglobin concentration in accordance with the commercial device. The flexible fNIRS system presented here not only provides a simple preparation process but also offers new ideas for daily cerebral state monitoring and prolonged clinical monitoring.

A Wearable Prefrontal Cortex Oxygen Saturation Measurement System Based on Near Infrared Spectroscopy

The measurement of blood oxygen saturation in the prefrontal cortex (PFC), especially during sleep, is of great significance for clinical research. Herein, we present a wearable PFC oxygen saturation measurement system using dual-wavelength functional near-infrared spectroscopy. The system is well designed for user-friendly donning and has the advantages of comfort, convenience, portability, and affordability. The performance of the proposed system is investigated by the calibration and experimental results. The wearable system has demonstrated great potential to conduct the physiological monitoring of PFC, and it can be widely deployed in daily life.

Emerging Wearable Interfaces and Algorithms for Hand Gesture Recognition: A Survey

Hands are vital in a wide range of fundamental daily activities, and neurological diseases that impede hand function can significantly affect quality of life. Wearable hand gesture interfaces hold promise to restore and assist hand function and to enhance human-human and human-computer communication. The purpose of this review is to synthesize current novel sensing interfaces and algorithms for hand gesture recognition, and the scope of applications covers rehabilitation, prosthesis control, sign language recognition, and human-computer interaction. Results showed that electrical, dynamic, acoustical/vibratory, and optical sensing were the primary input modalities in gesture recognition interfaces. Two categories of algorithms were identified: 1) classification algorithms for predefined, fixed hand poses and 2) regression algorithms for continuous finger and wrist joint angles. Conventional machine learning algorithms, including linear discriminant analysis, support vector machines, random forests, and non-negative matrix factorization, have been widely used for a variety of gesture recognition applications, and deep learning algorithms have more recently been applied to further facilitate the complex relationship between sensor signals and multi-articulated hand postures. Future research should focus on increasing recognition accuracy with larger hand gesture datasets, improving reliability and robustness for daily use outside of the laboratory, and developing softer, less obtrusive interfaces.

Control Methods for Transradial Prostheses Based on Remnant Muscle Activity and Its Relationship with Proprioceptive Feedback

The loss of a hand can significantly affect one's work and social life. For many patients, an artificial limb can improve their mobility and ability to manage everyday activities, as well as provide the means to remain independent. This paper provides an extensive review of available biosensing methods to implement the control system for transradial prostheses based on the measured activity in remnant muscles. Covered techniques include electromyography, magnetomyography, electrical impedance tomography, capacitance sensing, near-infrared spectroscopy, sonomyography, optical myography, force myography, phonomyography, myokinetic control, and modern approaches to cineplasty. The paper also covers combinations of these approaches, which, in many cases, achieve better accuracy while mitigating the weaknesses of individual methods. The work is focused on the practical applicability of the approaches, and analyses present challenges associated with each technique along with their relationship with proprioceptive feedback, which is an important factor for intuitive control over the prosthetic device, especially for high dexterity prosthetic hands.

Recent Progress in Wireless Sensors for Wearable Electronics

The development of wearable electronics has emphasized user-comfort, convenience, security, and improved medical functionality. Several previous research studies transformed various types of sensors into a wearable form to more closely monitor body signals and enable real-time, continuous sensing. In order to realize these wearable sensing platforms, it is essential to integrate wireless power supplies and data communication systems with the wearable sensors. This review article discusses recent progress in wireless technologies and various types of wearable sensors. Also, state-of-the-art research related to the application of wearable sensor systems with wireless functionality is discussed, including electronic skin, smart contact lenses, neural interfaces, and retinal prostheses. Current challenges and prospects of wireless sensor systems are discussed.

Functional Near Infrared Spectroscopy: Enabling Routine Functional Brain Imaging

Functional Near-Infrared Spectroscopy (fNIRS) maps human brain function by measuring and imaging local changes in hemoglobin concentrations in the brain that arise from the modulation of cerebral blood flow and oxygen metabolism by neural activity. Since its advent over 20 years ago, researchers have exploited and continuously advanced the ability of near infrared light to penetrate through the scalp and skull in order to non-invasively monitor changes in cerebral hemoglobin concentrations that reflect brain activity. We review recent advances in signal processing and hardware that significantly improve the capabilities of fNIRS by reducing the impact of confounding signals to improve statistical robustness of the brain signals and by enhancing the density, spatial coverage, and wearability of measuring devices respectively. We then summarize the application areas that are experiencing rapid growth as fNIRS begins to enable routine functional brain imaging.

Bundled-Optode Method in Functional Near-Infrared Spectroscopy

In this paper, a theory for detection of the absolute concentrations of oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR) from hemodynamic responses using a bundled-optode configuration in functional near-infrared spectroscopy (fNIRS) is proposed. The proposed method is then applied to the identification of two fingers (i.e., little and thumb) during their flexion and extension. This experiment involves a continuous-wave-type dual-wavelength (760 and 830 nm) fNIRS and five healthy male subjects. The active brain locations of two finger movements are identified based on the analysis of the t- and p-values of the averaged HbOs, which are quite distinctive. Our experimental results, furthermore, revealed that the hemodynamic responses of two-finger movements are different: The mean, peak, and time-to-peak of little finger movements are higher than those of thumb movements. It is noteworthy that the developed method can be extended to 3-dimensional fNIRS imaging.

Noninvasive Brain Physiology Monitoring for Extreme Environments: A Critical Review

Our ability to monitor the brain physiology is advancing; however, most of the technology is bulky, expensive, and designed for traditional clinical settings. With long-duration space exploration, there is a need for developing medical technologies that are reliable, low energy, portable, and semiautonomous. Our aim was to review the state of the art for noninvasive technologies capable of monitoring brain physiology in diverse settings. A literature review of PubMed and the Texas Medical Center library sites was performed using prespecified search criteria to identify portable technologies for monitoring physiological aspects of the brain physiology. Most brain-monitoring technologies require a moderate to high degree of operator skill. Some are low energy, but many require a constant external power supply. Most of the technologies lack the accuracy seen in gold standard measures, due to the need for calibration, but may be useful for screening or monitoring relative changes in a parameter. Most of the technologies use ultrasound or electromagnetic radiation as energy sources. There is an important need for further development of portable technologies that can be operated in a variety of extreme environments to monitor brain health.

Recent developments in near-infrared spectroscopy (NIRS) for the assessment of local skeletal muscle microvascular function and capacity to utilise oxygen

Purpose of review

Continuous wave near infrared spectroscopy (CW NIRS) provides non-invasive technology to measure relative changes in oxy- and deoxy-haemoglobin in a dynamic environment. This allows determination of local skeletal muscle O₂ saturation, muscle oxygen consumption (V˙O2) and blood flow. This article provides a brief overview of the use of CW NIRS to measure exercise-limiting factors in skeletal muscle.

Recent findings

NIRS parameters that measure O₂ delivery and capacity to utilise O₂ in the muscle have been developed based on response to physiological interventions and exercise. NIRS has good reproducibility and agreement with gold standard techniques and can be used in clinical populations where muscle oxidative capacity or oxygen delivery (or both) are impaired. CW NIRS has limitations including: the unknown contribution of myoglobin to the overall signals, the impact of adipose tissue thickness, skin perfusion during exercise, and variations in skin pigmentation. These, in the main, can be circumvented through appropriate study design or measurement of absolute tissue saturation.

Summary

CW NIRS can assess skeletal muscle O₂ delivery and utilisation without the use of expensive or invasive procedures and is useable in large population-based samples, including older adults.

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An overview of CW NIRS to measure O₂ utilisation and delivery is presented.

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CW NIRS is cheap, non-invasive, portable and useable in population-based samples.

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It is useful for understanding underlying mechanisms of deterioration in capacity.

A portable multi-channel wireless NIRS device for muscle activity real-time monitoring

Near-infrared spectroscopy (NIRS) is a relative new technology in monitoring muscle oxygenation and hemo-dynamics. This paper presents a portable multi-channel wireless NIRS device for real-time monitoring of muscle activity. The NIRS sensor is designed miniaturized and modularized, to make multi-site monitoring convenient. Wireless communication is applied to data transmission avoiding of cumbersome wires and the whole system is highly integrated. Special care is taken to eliminate motion artifact when designing the NIRS sensor and attaching it to human skin. Besides, the system is designed with high sampling rate so as to monitor rapid oxygenation changes during muscle activities. Dark noise and long-term drift tests have been carried out, and the result indicates the device has a good performance of accuracy and stability. In vivo experiments including arterial occlusion and isometric voluntary forearm muscle contraction were performed, demonstrating the system has the ability to monitor muscle oxygenation parameters effectively even in exercise.