Evaluating the Impact of the Number of Access Points in Mobile Robots Localization Using Artificial Neural Networks

Localization is information of fundamental importance to carry out various tasks in the mobile robotic area. The exact degree of precision required in the localization depends on the nature of the task. The GPS provides global position estimation but is restricted to outdoor environments and has an inherent imprecision of a few meters. In indoor spaces, other sensors like lasers and cameras are commonly used for position estimation, but these require landmarks (or maps) in the environment and a fair amount of computation to process complex algorithms. These sensors also have a limited field of vision. Currently, Wireless Networks (WN) are widely available in indoor environments and can allow efficient global localization that requires relatively low computing resources. However, the inherent instability in the wireless signal prevents it from being used for very accurate position estimation. The growth in the number of Access Points (AP) increases the overlap signals areas and this could be a useful means of improving the precision of the localization. In this paper we evaluate the impact of the number of Access Points in mobile nodes localization using Artificial Neural Networks (ANN). We use three to eight APs as a source signal and show how the ANNs learn and generalize the data. Added to this, we evaluate the robustness of the ANNs and evaluate a heuristic to try to decrease the error in the localization. In order to validate our approach several ANNs topologies have been evaluated in experimental tests that were conducted with a mobile node in an indoor space.

Improving backdrivability in geared rehabilitation robots

Many rehabilitation robots use electric motors with gears. The backdrivability of geared drives is poor due to friction. While it is common practice to use velocity measurements to compensate for kinetic friction, breakaway friction usually cannot be compensated for without the use of an additional force sensor that directly measures the interaction force between the human and the robot. Therefore, in robots without force sensors, subjects must overcome a large breakaway torque to initiate user-driven movements, which are important for motor learning. In this technical note, a new methodology to compensate for both kinetic and breakaway friction is presented. The basic strategy is to take advantage of the fact that, for rehabilitation exercises, the direction of the desired motion is often known. By applying the new method to three implementation examples, including drives with gear reduction ratios 100-435, the peak breakaway torque could be reduced by 60-80%.

A novel paradigm for patient-cooperative control of upper-limb rehabilitation robots

Early intervention and intensive therapy improve the outcome of neuromuscular rehabilitation. There are indications that where a patient is motivated and premeditates their movement, the recovery is more effective. Therefore, a strategy for patient-cooperative control of rehabilitation devices for upper extremities is proposed and evaluated. The strategy is based on the minimal intervention principle allowing an efficient exploitation of task space redundancies and resulting in user-driven movement trajectories. The patient's effort is taken into consideration by enabling the machine to comply with forces exerted by the user. The interaction is enhanced through a multimodal display and a virtually generated environment that includes haptic, visual and sound modalities.

A robotic system to train activities of daily living in a virtual environment

In the past decade, several arm rehabilitation robots have been developed to assist neurological patients during therapy. Early devices were limited in their number of degrees of freedom and range of motion, whereas newer robots such as the ARMin robot can support the entire arm. Often, these devices are combined with virtual environments to integrate motivating game-like scenarios. Several studies have shown a positive effect of game-playing on therapy outcome by increasing motivation. In addition, we assume that practicing highly functional movements can further enhance therapy outcome by facilitating the transfer of motor abilities acquired in therapy to daily life. Therefore, we present a rehabilitation system that enables the training of activities of daily living (ADL) with the support of an assistive robot. Important ADL tasks have been identified and implemented in a virtual environment. A patient-cooperative control strategy with adaptable freedom in timing and space was developed to assist the patient during the task. The technical feasibility and usability of the system was evaluated with seven healthy subjects and three chronic stroke patients.

A self-developed and constructed robot for minimally invasive cochlear implantation

Conclusion: A robot built specifically for stereotactic cochlear implantation provides equal or better accuracy levels together with a better integration into a clinical environment, when compared to existing approaches based on industrial robots. Objectives: To evaluate the technical accuracy of a robotic system developed specifically for lateral skull base surgery in an experimental setup reflecting the intended clinical application. The invasiveness of cochlear electrode implantation procedures may be reduced by replacing the traditional mastoidectomy with a small tunnel slightly larger in diameter than the electrode itself. Methods: The end-to-end accuracy of the robot system and associated image-guided procedure was evaluated on 15 temporal bones of whole head cadaver specimens. The main components of the procedure were as follows: reference screw placement, cone beam CT scan, computer-aided planning, pair-point matching of the surgical plan, robotic drilling of the direct access tunnel, and post-operative cone beam CT scan and accuracy assessment. Results: The mean accuracy at the target point (round window) was 0.56 ± 41 mm with an angular misalignment of 0.88 ± 0.41°. The procedural time of the registration process through the completion of the drilling procedure was 25 ± 11 min. The robot was fully operational in a clinical environment.

Effects of dose reduction on the detectability of standardized radiolucent lesions in digital panoramic radiography

Dose reduction in digital panoramic radiography was studied. Intentional underexposure was performed with the Orthophos DS while six different human mandibles were radiographed. Exposure settings were 69 kV/15 mA (standard), 64 kV/16 mA, and 60 kV/16 mA. Standardized spherical defects, each either 1 or 1.25 mm in diameter, were simulated in 288 of 432 images, and seven observers decided whether defects were present or not. Areas under the receiver operating characteristics curves were calculated. They showed no significant differences in the detectability of the 1-mm defect at 69, 64, or 60 kV. For the 1.25-mm defect, no difference was found between the 69 and 60 kV images, but a statistically significant different detectability was found for 64 kV images in comparison with both 69 and 60 kV images. A dose reduction of up to 43% was ascertained with a Pedo-RT-Humanoid phantom when panoramic radiography was performed at 60 kV/16 mA. The conclusion is that with the Orthophos DS, it seems possible to reduce the dose rate of x-rays without loss of diagnostic quality in the case of radiolucent changes.

Estimation of tool pose based on force-density correlation during robotic drilling

The application of image-guided systems with or without support by surgical robots relies on the accuracy of the navigation process, including patient-to-image registration. The surgeon must carry out the procedure based on the information provided by the navigation system, usually without being able to verify its correctness beyond visual inspection. Misleading surrogate parameters such as the fiducial registration error are often used to describe the success of the registration process, while a lack of methods describing the effects of navigation errors, such as those caused by tracking or calibration, may prevent the application of image guidance in certain accuracy-critical interventions. During minimally invasive mastoidectomy for cochlear implantation, a direct tunnel is drilled from the outside of the mastoid to a target on the cochlea based on registration using landmarks solely on the surface of the skull. Using this methodology, it is impossible to detect if the drill is advancing in the correct direction and that injury of the facial nerve will be avoided. To overcome this problem, a tool localization method based on drilling process information is proposed. The algorithm estimates the pose of a robot-guided surgical tool during a drilling task based on the correlation of the observed axial drilling force and the heterogeneous bone density in the mastoid extracted from 3-D image data. We present here one possible implementation of this method tested on ten tunnels drilled into three human cadaver specimens where an average tool localization accuracy of 0.29 mm was observed.

Estimating the patient's contribution during robot-assisted therapy

Robot-assisted therapy has become increasingly common in neurorehabilitation. Sophisticated controllers have been developed for robots to assist and cooperate with the patient. It is difficult for the patient to judge to what extent the robot contributes to the execution of a movement. Therefore, methods to comprehensively quantify the patient's contribution and provide feedback are of key importance. We developed a method comprehensively to estimate the patient's contribution by combining kinematic measures and the motor assistance applied. Inverse dynamic models of the robot and the passive human arm calculate the required torques to move the robot and the arm and build, together with the recorded motor torque, a metric (in percentage) that represents the patient's contribution to the movement. To evaluate the developed metric, 12 nondisabled subjects and 7 patients with neurological problems simulated instructed movement contributions. The results are compared with a common performance metric. The estimation shows very satisfying results for both groups, even though the arm model used was strongly simplified. Displaying this metric to patients during therapy can potentially motivate them to actively participate in the training.

ARMin III – arm therapy exoskeleton with an ergonomic shoulder actuation

Rehabilitation robots have become important tools in stroke rehabilitation. Compared to manual arm training, robot-supported training can be more intensive, of longer duration and more repetitive. Therefore, robots have the potential to improve the rehabilitation process in stroke patients. Whereas a majority of previous work in upper limb rehabilitation robotics has focused on end-effector-based robots, a shift towards exoskeleton robots is taking place because they offer a better guidance of the human arm, especially for movements with a large range of motion. However, the implementation of an exoskeleton device introduces the challenge of reproducing the motion of the human shoulder, which is one of the most complex joints of the body. Thus, this paper starts with describing a simplified model of the human shoulder. On the basis of that model, a new ergonomic shoulder actuation principle that provides motion of the humerus head is proposed, and its implementation in the ARMin III arm therapy robot is described. The focus lies on the mechanics and actuation principle. The ARMin III robot provides three actuated degrees of freedom for the shoulder and one for the elbow joint. An additional module provides actuated lower arm pro/supination and wrist flexion/extension. Five ARMin III devices have been manufactured and they are currently undergoing clinical evaluation in hospitals in Switzerland and in the United States.

Effects of arm training with the robotic device ARMin I in chronic stroke: three single cases

BACKGROUND: Several clinical studies on chronic stroke conducted with end-effector-based robots showed improvement of the motor function in the affected arm. Compared to end-effector-based robots, exoskeleton robots provide improved guidance of the human limb and are better suited to train task-oriented movements with a large range of motions. OBJECTIVE: To test whether intensive arm training with the arm exoskeleton ARMin I is feasible with chronic-stroke patients and whether it improves motor function in the paretic arm. METHODS: Three single cases with chronic hemiparesis resulting from unilateral stroke (at least 14 months after stroke). A-B design with 2 weeks of multiple baseline measurements (A), 8 weeks of training (B) with repetitive measurements and a follow-up measurement 8 weeks after training. The training included shoulder and elbow movements with the robotic rehabilitation device ARMin I. Two subjects had three 1-hour sessions per week and 1 subject received five 1-hour sessions per week. The main outcome measurement was the upper-limb part of the Fugl-Meyer Assessment (FMA). RESULTS: The ARMin training was well tolerated by the patients, and the FMA showed moderate, but significant improvements for all 3 subjects (p < 0.05). Most improvements were maintained 8 weeks after discharge. CONCLUSIONS: This study indicates that intensive training with an arm exoskeleton is feasible with chronic-stroke patients. Moderate improvements were found in all 3 subjects, thus further clinical investigations are justified.

Temperature Prediction Model for Bone Drilling Based on Density Distribution and In Vivo Experiments for Minimally Invasive Robotic Cochlear Implantation

Surgical robots have been proposed ex vivo to drill precise holes in the temporal bone for minimally invasive cochlear implantation. The main risk of the procedure is damage of the facial nerve due to mechanical interaction or due to temperature elevation during the drilling process. To evaluate the thermal risk of the drilling process, a simplified model is proposed which aims to enable an assessment of risk posed to the facial nerve for a given set of constant process parameters for different mastoid bone densities. The model uses the bone density distribution along the drilling trajectory in the mastoid bone to calculate a time dependent heat production function at the tip of the drill bit. Using a time dependent moving point source Green's function, the heat equation can be solved at a certain point in space so that the resulting temperatures can be calculated over time. The model was calibrated and initially verified with in vivo temperature data. The data was collected in minimally invasive robotic drilling of 12 holes in four different sheep. The sheep were anesthetized and the temperature elevations were measured with a thermocouple which was inserted in a previously drilled hole next to the planned drilling trajectory. Bone density distributions were extracted from pre-operative CT data by averaging Hounsfield values over the drill bit diameter. Post-operative [Formula: see text]CT data was used to verify the drilling accuracy of the trajectories. The comparison of measured and calculated temperatures shows a very good match for both heating and cooling phases. The average prediction error of the maximum temperature was less than 0.7 °C and the average root mean square error was approximately 0.5 °C. To analyze potential thermal damage, the model was used to calculate temperature profiles and cumulative equivalent minutes at 43 °C at a minimal distance to the facial nerve. For the selected drilling parameters, temperature elevation profiles and cumulative equivalent minutes suggest that thermal elevation of this minimally invasive cochlear implantation surgery may pose a risk to the facial nerve, especially in sclerotic or high density mastoid bones. Optimized drilling parameters need to be evaluated and the model could be used for future risk evaluation.

Image-Guided Orthopaedic Surgery

Image-guided surgery systems are increasingly being used during orthopaedic interventions. The aim of this chapter is to present the basic elements of these image-guided orthopaedic surgery (IGOS) devices and to review examples of preoperative or intra-operative imaging modalities, of trackers for navigation systems, of different surgical robots, and of methods for registration as well as referencing. IGOS modules that have been realised for different surgical procedures will be presented.

Computer-Assisted Orthopedic Surgery: Current State and Future Perspective

Introduced about two decades ago, computer-assisted orthopedic surgery (CAOS) has emerged as a new and independent area, due to the importance of treatment of musculoskeletal diseases in orthopedics and traumatology, increasing availability of different imaging modalities, and advances in analytics and navigation tools. The aim of this paper is to present the basic elements of CAOS devices and to review state-of-the-art examples of different imaging modalities used to create the virtual representations, of different position tracking devices for navigation systems, of different surgical robots, of different methods for registration and referencing, and of CAOS modules that have been realized for different surgical procedures. Future perspectives will also be outlined.