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g. functional lenses that allow focus adjustment.An augmented reality (AR)-assisted surgical navigation system was developed for epidural needle intervention. The system includes three components a virtual reality-based surgical planning software, a patient and tool tracking system, and an AR-based surgical navigation system. A three-dimensional (3D) path plan for the epidural needle was established on the preoperative computed tomography (CT) image. The plan is then registered to the intraoperative space by 3D models of the target vertebrae using skin markers and real-time tracking information. In the procedure, the plan and tracking information are transmitted to the head-mounted display (HMD) through a wireless network such that the device directly visualizes the plan onto the back surface of the patient. The physician determines the entry point and inserts the needle into the target based on the direct visual guidance of the system. An experiment was conducted to validate the system using two torso phantoms that mimic human respiration. The experimental results demonstrated that the time and the number of X-rays required for needle insertion were significantly decreased by the proposed method (43.6±20.55sec, 2.9±1.3times) compared to those of the conventional fluoroscopy-guided approach (124.5 ± 46.7s, 9.3±2.4times), whereas the average targeting errors were similar in both cases. The proposed system may potentially decrease ionizing radiation exposure not only to the patient but also to the medical team.In conventional Minimally Invasive Surgery, the surgeon conducts the operation while a human or robot holds the laparoscope. Laparoscope control is returned to the surgeon in teleoperated camera holding robots, but simultaneously controlling the laparoscope and surgical tools might be cognitively demanding. On the other hand, fully automated camera holders are still limited in their performance. To help the surgeon to better focus on the main operation while maintaining their control authority, we propose an automatic laparoscope zoom factor control framework for Robot-Assisted Minimally Invasive Surgery. In this paper, we present the perception section of the framework. It extracts and uses the surgical tool's geometric characteristics to adjust the laparoscope's zoom factor, without any artificial markers. The acceptable range and tooltip's position frequency during operations are analysed based on the gallbladder removal surgery dataset (Cholec80). The common range and tooltip's heatmap are identified and presented quantitatively.In this work we are interested in to assess the effectiveness of a impedance control applied to a lower limb exoskeleton that assists a individual with weakness to perform the swing movement of gait. To this, we carried out simulations using a human-exoskeleton interaction model from OpenSim, a forward dynamics-based simulation algorithm from MATLAB and experimental data from a subject walking on a treadmill. Ro 61-8048 clinical trial The results proved that the control is efficient and capable of providing the necessary complementary torque so that the person can complete the movement with dexterity.Lower limb exoskeletons have complex dynamics that mimic human motion. They need to be able to replicate lower limb motion such as walking. The trajectory of the exoskeleton joints and the control signal generated are essential to the system's operation. Current learning from demonstration methods has only been combined with linear quadratic regulators; this limits the applicability of processes since most robotic systems have non-linear dynamics. The Asynchronous Multi-Body Framework simulates the dynamics and allows for real-time control. Eleven gait cycle demonstrations were recorded from volunteers using motion capture and encoded using Task Parameterized Gaussian mixture models. An iterative linear quadratic regulator is used to find an optimal control signal to drive the exoskeleton joints through the desired trajectories. A PD controller is added as a feed-forward control component for unmodeled dynamics and optimized using the Bayesian Information Criterion. We show how the trajectory is learned, and the control signal is optimized by reducing the required bins for learning. The framework presented produces optimal control signals to allow the exoskeleton's legs to follow human motion demonstrations.

Stress fractures are common overuse running injuries. Individuals with stress fractures exhibit running biomechanics characterized by elevated impact peak and loading rate. While elevated impact peak and loading rate are associated with stress fractures, there are few established metrics used to identify the presence of stress fractures in individuals. Here this study aims to exploit the linear relationship between the impact peak and loading rate to establish a metric to help identify individuals with stress fractures. We hypothesize that the ratio between the impact peak and loading rate will serve as a metric to delineate between healthy controls and those with stress fractures.

Fifteen healthy controls and 11 individuals with stress fractures performed a running protocol. A linear regression model fit to the stress fracture impact peak and loading rate data produced a lower 95% confidence limit boundary that served as the demarcation line between the two groups.

Individuals with stress fractures tended to reside above the line with the line accurately classifying 82% of the individuals with stress fractures.

The analysis supported the hypothesis and demonstrated how the relationship between impact peak and loading rate can help identify the presence of stress fractures in individuals.Clinical Relevance- The relationship between impact peak and loading rate has the potential to serve as clinically useful metric to identify stress fractures during running.

The analysis supported the hypothesis and demonstrated how the relationship between impact peak and loading rate can help identify the presence of stress fractures in individuals.Clinical Relevance- The relationship between impact peak and loading rate has the potential to serve as clinically useful metric to identify stress fractures during running.The robotic-assisted percutaneous coronary intervention is an emerging technology with great potential to solve the shortcomings of existing treatments. However, the current robotic systems can not manipulate two guidewires or ballons/stents simultaneously for coronary bifurcation lesions. This paper presents VasCure, a novel bio-inspired vascular robotic system, to deliver two guidewires and stents into the main branch and side branch of bifurcation lesions in sequence. The system is designed in master-slave architecture to reduce occupational hazards of radiation exposure and orthopedic injury to interventional surgeons. The slave delivery device has one active roller and two passive rollers to manipulate two interventional devices. The performance of the VasCure was verified by in vitro and in vivo animal experiments. In vitro results showed the robotic system has good accuracy to deliver guidewires and the maximum error is 0.38mm. In an animal experiment, the interventional surgeon delivered two guidewires and balloons to the left circumflex branch and the left anterior descending branch of the pig, which confirmed the feasibility of the vascular robotic system.Percutaneous coronary intervention (PCI) has gradually become the most common treatment of coronary artery disease (CAD) in clinical practice due to its advantages of small trauma and quick recovery. However, the availability of hospitals with cardiac catheterization facilities and trained interventionalists is extremely limited in remote and underdeveloped areas. Remote vascular robotic system can assist interventionalists to complete operations precisely, and reduce occupational health hazards occurrence. In this paper, a bionic remote vascular robot is introduced in detail from three parts mechanism, communication architecture, and controller model. Firstly, human finger-like mechanisms in vascular robot enable the interventionalists to advance, retract and rotate the guidewires or balloons. Secondly, a 5G-based communication system is built to satisfy the end-to-end requirements of strong data transmission and packet priority setting in remote robot control. link2 Thirdly, a generalized predictive controller (GPC) is developed to suppress the effect of time-varying network delay and parameter identification error, while adding a designed polynomial compensation module to reduce tracking error and improve system responsiveness. Then, the simulation experiment verifies the system performance in comparison with different algorithms, network delay, and packet loss rate. Finally, the improved control system conducted PCI on an experimental pig, which reduced the delivery integral absolute error (IAE) by at least 20% compared with traditional methods.Table tennis is a popular sport for forearm amputees. However, forearm amputees with limited pronation and supination movements cannot switch the racket angle properly for forehand and backhand drives. This paper reports a table tennis prosthetic hand controlled based on distance measurement using a ToF Sensor. The developed hand can switch the racket angle between forehand drive and backhand drive based on the distance between the wrist and the trunk or upper arm measured by the ToF sensor attached to an electric wrist. The participant with forearm amputation could play table tennis with the developed hand in the test play. The racket angle was switched to the appropriate angle for the forehand drive and the backhand drive, and the participant could return a ball 6.3 times in 10 seconds. The satisfaction of the participant with the prosthetic hand was good.Acquired brain injury (ABI) resulting in hemiplegia, is one of the leading causes of gait and balance deficits in adults. Gait and balance deficits include reduced momentum for forward progression, reduced step length, increased spatial and temporal asymmetry, and decreased speed; resulting in reduced functional ambulation, activities of daily living, and quality of life. link3 Wearable lower extremity robotic exoskeletons (REs) are becoming an effective method for gait neurorehabilitation in individuals with ABI. REs can provide high dose, consistent, goal-directed repetition of movements as well as balance & stability for individuals with ABI. The objective of this study is to understand the effect of RE gait training using center of pressure (COP) displacement, temporal & spatial parameters, and functional outcomes for individuals with ABI. The results from this investigation show improved anterior-posterior COP displacement & rate of progression, spatial symmetry, step length, walking speed, and decreased time during the gait cycle. These preliminary results suggest that high dose, repetitive gait training using robotic exoskeletons has the potential to induce recovery of function in adults diagnosed with ABI.In stroke patients, sensory loss often reduces the sensation of ground contact, which impairs motor learning during rehabilitation. In our previous study, we proposed a vibro-tactile biofeedback system (which we called the perception-empathy biofeedback system) for gait rehabilitation. The results of our 9-week pilot clinical test suggested that patients who had reached the autonomous phase in gait learning had difficulty noticing the external vibratory feedback provided by the biofeedback system, leading to ineffective intervention. We considered the possibility that slower walking speed might return the patient to the association phase and allow patients to improve their gait according to the sensory feedback provided. Thus, in this research, a method based on reducing walking speed to guide patients' attention was derived. A pilot clinical trial shows that there is a statistically significant increase of ankle dorsiflexion in the initial contact phase and increase of ankle plantarflexion in the push-off phase after vibro-tactile biofeedback system intervention with speed reduction, compared to intervention without speed reduction.