Xinyu Guan

The quantitative assessment of human energy expenditure is of critical importance to clinical diagnostics, nutritional management, and sports science. As the gold standard methodology, indirect calorimetry determines energy expenditure through the measurement of oxygen consumption and carbon dioxide production. However, translating these principles into robust monitoring systems involves complex engineering hurdles. This review organizes the technical discussion around three interrelated challenges inherent to indirect calorimetry systems: (1) intrinsic hardware limitations in gas sensors, (2) complexities in data processing, and (3) discrepancies between laboratory and field environments. The discussion begins with the fundamental principles of energy expenditure calculation, followed by an in-depth analysis of key sensor technologies (e.g., turbine and differential pressure flowmeters; electrochemical and paramagnetic oxygen sensors; non-dispersive infrared carbon dioxide sensors). Subsequently, particular attention is given to algorithmic solutions for mitigating hardware deficiencies—such as noise, latency, and drift—as well as multi-sensor fusion and calibration techniques. Crucially, this review addresses the practical obstacles hindering the transition to real-world applications, encompassing economic viability, regulatory compliance, user usability, and long-term maintenance. The review concludes that while hardware limitations persist, the synergistic application of sophisticated algorithms and the resolution of practical implementation hurdles are indispensable for advancing measurement accuracy and facilitating the transition of metabolic monitoring from controlled laboratory settings to real-world applications in personalized health and performance tracking.

Crutches are of extensive applications in the field of rehabilitation. Comprehensively analyzing the ground reaction forces (GRFs) on both crutches and feet can evaluate the patients' walking function recovery. Given more force platforms are needed in clinical evaluation for the crutch gait than the normal gait pattern and the resulting high cost, this research proposes a method to predict both ground and foot GRFs during walking with crutches, using kinematic information from motion capture trials. We collected force and motion data, built a musculoskeletal model in Opensim, and computed joint angles and moments of crutch gait. Different Artificial Neural Networks (ANN), including Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), and Long Short-Term Memory network (LSTM) were established to test their predictive ability using Leave-One-Subject-Out(LOSO) cross validation method. LSTM model showed the strongest agreement, with r = 0.961±0.050 and nRMSE=13.8 % in the vertical direction of the left foot. The LSTM model was more accurate than the CNN model and more robust than the MLP model in this component. In average of different directions, LSTM model has r = 0.656±0.362 and nRMSE=30.3 %. Further verification of the prediction was executed by computing joint moments. The LSTM model showed great application prospects in crutch gait GRF analysis.

The health condition can be reflected by human respiration monitoring, which requires the cooperation of various sensors including flow and concentration sensors. Based on the signal characteristics of the respiratory process, several modeling methods were used to reduce measurement error and improve response speed. The autoregressive exogenous (ARX) model resulted in smoother data from the turbine flowmeter and enabled 96.2% of tests to have an error of less than 3%. Wiener filtering significantly reduced the response time of the gas concentration sensors. The response time was shortened from 140 ms to 100 ms for the CO ₂ sensor, and 220 ms to 100 ms for the O ₂ sensor. The end-tidal gas concentration characteristics were used to perform an alignment criterion between the different sensors to calculate end-tidal oxygen (F _ET O ₂ ) and end-tidal carbon dioxide (F _ET CO ₂ ) in comparison with Cosmed K5, which shows clinically insignificant differences according to the Bland-Altman analysis. This paper provides a comprehensive modeling approach for the breath-by-breath (BBB) respiratory measurement method, enhancing the system’s performance through sensor modeling and sensor signal alignment. Results indicate potential for practical application and scalability, offering an effective reference for similar systems.

The objective of this paper is to identify dynamic parameters of the human-exoskeleton system (HES) with the motor torque data considering modeling the passive elastic joint torque of the user. Based on a lower limb exoskeleton prototype we recently developed, the dynamics of the joint actuators and two degrees of freedom link-based swing leg are firstly modeled. The passive elasticity of the human joint is modeled by double-exponential equations. Systematic experiments are then conducted, during which the motor current is measured to compute the motor torque for identification. Finally, the dynamic parameters of the joint actuators, the exoskeleton leg and the human-exoskeleton leg are successively identified. The identification is implemented through the off-line inverse dynamic model simulation with the measured motor torque data. A consistent tendency is found between the simulated motor torque after identification and the measured one. This demonstrates the validity of the identification method proposed. This paper provides a systemic method of identifying the HES with the motor torque data and enriches the experimental proof that the double-exponential model is feasible to describe the passive elastic joint torque.

Hikers and soldiers usually walk up and down slopes with a load carriage, causing injuries of the musculoskeletal system, especially during a prolonged load journey. The slope walking has been reported to lead to higher leg extensor muscle activities and joint moments. However, most of the studies investigated muscle activities or joint moments during slope walking without load carriage or only investigated the joint moment changes and muscle activities with load carriages during level walking. Whether the muscle activation such as the signal amplitude is influenced by the mixed factor of loads and grades and whether the influence of the degrees of loads and grades on different muscles are equal have not yet been investigated. To explore the effects of backpack loads on leg muscle activation during slope walking, ten young male participants walked at 1.11 m/s on a treadmill with different backpack loads (load masses: 0, 10, 20, and 30 kg) during slope walking (grade: 0, 3, 5, and 10°). Leg muscles, including the gluteus maximus (GM), rectus femoris (RF), hamstrings (HA), anterior tibialis (AT), and medial gastrocnemius (GA), were recorded during walking. The hip, knee, and ankle extensor muscle activations increased during the slope walking, and the hip muscles increased most among hip, knee, and ankle muscles (GM and HA increased by 46% to 207% and 110% to 226%, respectively, during walking steeper than 10° across all load masses (GM: p = 1.32 × 10⁻⁸ and HA: p = 2.33 × 10⁻¹⁶)). Muscle activation increased pronouncedly with loads, and the knee extensor muscles increased greater than the hip and ankle muscles (RF increased by 104% to 172% with a load mass greater than 30 kg across all grades (RF: p = 8.86 × 10⁻⁷)). The results in our study imply that the hip and knee muscles play an important role during slope walking with loads. The hip and knee extension movements during slope walking should be considerably assisted to lower the muscle activations, which will be useful for designing assistant devices, such as exoskeleton robots, to enhance hikers’ and soldiers’ walking abilities.

SIGNIFICANCE: Investigation of the mechanism and the role of melanopsin in lens‐induced myopia is necessary to find out potential targets in the prevention of myopia development. PURPOSE: We aimed to study the effect and mechanism of retinal melanopsin on lens‐induced myopia in guinea pigs, as well as the interactions between melanopsin and other myopic regulation neurotransmitters such as dopamine and melatonin, and to explore the possible role of melanopsin in the prevention of myopia development. METHODS: Twenty‐day‐old tricolor guinea pigs were randomly divided into four groups: control group, defocus group, defocus + AA92593 group, and defocus + dimethyl sulfoxide (DMSO) group. The defocus eyes wore −6.00 D lens. In the defocus + AA92593 group, the vitreous cavities were injected with melanopsin antagonist AA92593. In the defocus + DMSO group, the vitreous cavities were injected with 5% DMSO as the administration control. The expression of retinal melanopsin protein was measured with immunofluorescence staining and Western blot. The content of dopamine and melatonin in the retina was determined by the high‐performance liquid chromatography electrochemical method. RESULTS: Compared with the defocus group, intravitreal injection of AA92593 resulted in increased axial length of the defocus eyes (defocus, 8.05 ± 0.09 mm; defocus + AA92593, 8.15 ± 0.11 mm; P =. 008), lower refractive degree (defocus, −1.98 ± 0.82 D; defocus + AA92593, −2.59 ± 0.97 D; P =. 05), decreased relative expression of retinal melanopsin protein (defocus, 0.67 ± 0.11; defocus + AA92593, 0.20 ± 0.06; P <. 0001), and increased melatonin content in the defocus eyes (defocus, 0.38 ± 0.09 ng/mg; defocus + AA92593, 0.55 ± 0.13 ng/mg; P =. 01), but it had no obvious effect on dopamine content (defocus, 0.64 ± 0.18 ng/mg; defocus + AA9259, 0.61 ± 0.17 ng/mg; P >. 99). The melatonin content of retina in the defocus + AA92593 group was correlated with refractive error (Pearson correlation coefficient = −0.68, P =. 006) and eye axis length (Pearson correlation coefficient = 0.74, P =. 02). CONCLUSIONS: Retinal melanopsin has inhibitory effect on lens‐induced myopia development in guinea pigs, and such effect may be related to retinal melatonin.

To improve the optimization quality, stability, and speed of convergence of wolf pack algorithm, an adaptive shrinking grid search chaotic wolf optimization algorithm using standard deviation updating amount (ASGS-CWOA) was proposed. First of all, a strategy of adaptive shrinking grid search (ASGS) was designed for wolf pack algorithm to enhance its searching capability through which all wolves in the pack are allowed to compete as the leader wolf in order to improve the probability of finding the global optimization. Furthermore, opposite-middle raid method (OMR) is used in the wolf pack algorithm to accelerate its convergence rate. Finally, “Standard Deviation Updating Amount” (SDUA) is adopted for the process of population regeneration, aimed at enhancing biodiversity of the population. The experimental results indicate that compared with traditional genetic algorithm (GA), particle swarm optimization (PSO), leading wolf pack algorithm (LWPS), and chaos wolf optimization algorithm (CWOA), ASGS-CWOA has a faster convergence speed, better global search accuracy, and high robustness under the same conditions.

This paper introduces the analysis, design and preliminary evaluation of a self-integrated parallel elastic actuator (PEA) with an electric motor and a flat spiral spring in parallel to drive the hip joint of lower limb exoskeletons for power-efficient walking assistance. Firstly, we quantitatively analyze the reason why the parallel elasticity (PE) placed at the sagittal hip joint can reduce the motor power requirement during walking assistance, which contributes to the theory of PEA development and application. The design of the PEA is then introduced in detail. The novelty of the design is that the actuator is reduced in size by integrating the spring into the motor, and the requirement of spring stiffness is significantly reduced by placing the spring directly parallel to the motor shaft. Furthermore, both the simulation based on dynamic modeling and benchtop experiment are conducted preliminarily to evaluate the performance of the PEA with nine spring stiffnesses in a range from 0 - 5.29 mN·m/rad regarding two indexes including the average and maximum positive electrical power of the motor. Their results show that the two indexes become smaller when the PE is attached and decrease as the spring stiffness increases. When the PE with a stiffness of 5.29 mN·m/rad is attached, the actuator obtains the largest reduction rate of 11.99 and 16.84 % in the average (root mean square) and maximum positive electrical power of the motor in the simulation and 10.3 and 26.25 % in the experiment, respectively. Those results provide evidence for the applicability of the newly designed PEA in driving a lower limb exoskeleton with high power efficiency during walking assistance for paraplegic patients with complete loss in walking ability.

Geared motor-driven lower limb exoskeletons (LLEs) are widely researched to assist paraplegic patients with spinal cord injury in recovering locomotion ability. In order to achieve a compact exoskeleton joint design while avoiding increasing the mechanical complexity of the exoskeleton frame, this study presents a design of an LLE with compact and modular actuation. A synchronous drive and a gear drive as transmissions are used to distribute hip and knee actuators, respectively, ensuring a compact axial length. The modular design of joint actuators enables it simple to separately design or select the ergonomic exoskeleton frames. A paradigm of the LLE design is comprehensively provided, including the requirement analysis, mechanical, electrical and control system design, which can be a reference of the early development of the exoskeleton prototype. The performance of the LLE is preliminarily validated by the benchtop tests including the closed-loop speed bandwidth test and the swing test and one healthy human subject experiment including walking with the LLE disenabling all motors and walking assisted by the LLE. The results of the benchtop tests validate that the LLE has enough bandwidth of closed-loop speed, satisfactory repeatability, high precision, good antijamming capability and strong torque capacity. The results of the healthy human subject experiment validate a harmonic interaction and a good integration between the user and the ergonomic mechanical system, good performance of the electrical and control system in joints motion control of the LLE. The prototype of the LLE smoothly and successfully assists the healthy human subject in walking on the level ground. The proposed LLE is promising to be applied to assist paraplegic patients in recovering the walking ability.

With the popularization of rehabilitation robots, it is necessary to develop quantitative motor function assessment methods for patients with a stroke. To make the assessment equipment easier to use in clinics and combine the assessment methods with the rehabilitation training process, this paper proposes an anthropomorphic rehabilitation robot based on the basic movement patterns of the upper limb, point‐to‐point reaching and circle drawing movement. This paper analyzes patients’ movement characteristics in aspects of movement range, movement accuracy, and movement smoothness and the output force characteristics by involving 8 patients. Besides, a quantitative assessment method is also proposed based on multivariate fitting methods. It can be concluded that the area of the real trajectory and movement accuracy during circle drawing movement as well as the ratio of force along the sagittal axis in backward point‐to‐point movement are the unique parameters that are different remarkably between stroke patients and healthy subjects. The fitting function has a high goodness of fit with the Fugl‐Meyer scores for the upper limb (R² = 0.91, p = 0.015), which demonstrates that the fitting function can be used to assess patients’ upper limb movement function. The indicators are recorded during training movement, and the fitting function can calculate the scores immediately, which makes the functional assessment quantitative and timely. Combining the training process and assessment, the quantitative assessment method will farther expand the application of rehabilitation robots.