The ability to control balance and stability are essential to prevent falls during locomotion. Maintenance of stable locomotion is challenging especially when complicated by amputation and prosthesis use. Humans employ several motor strategies to maintain stability during walking on complex terrain: decreasing walking speed, adjusting stride length and stance width, lowering the center of mass, and prolonging the double support time. The mechanisms of selecting these motor strategies by the primary motor cortex are unknown and cannot be studied directly in humans. There is also little information about dynamic stability of prosthetic gait with bone-anchored prostheses, which are thought to provide sensory feedback to the amputee through osseoperception. Therefore, the Specific Aims of my research were to (1) evaluate dynamic stability and the activity of the primary motor cortex during walking with different constraints on the base of support and (2) develop an animal model to evaluate mechanics and stability of prosthetic gait with a bone-anchored prosthesis. To address these aims, I developed a feline model that allows for investigating (1) the role of the primary motor cortex in regulation of dynamic stability of intact locomotion, (2) skin and bone integration with a percutaneous porous titanium implant facilitating prosthetic attachment, and (3) dynamic stability of walking on a bone-anchored prosthesis. The results of Specific Aim 1 demonstrated that the area and shape of the base of support influence the margins of dynamic stability during quadrupedal walking. For example, I found that the animal is dynamically unstable in the sagittal plane and frontal plane (although to a lesser degree) during a double-support by a forelimb and the contralateral hindlimb. Elevated neuronal activity from the right forelimb representation in the primary motor cortex during these phases suggests that the motor cortex may contribute to selection of paw placement location and thus to regulation of stability. The results of Specific Aim 2 on the development of skin-integrated bone-anchored prostheses demonstrated the following. Skin ingrowth into 3 types of porous titanium pylons (pore sizes 40-100 μm and 100-160 μm and nano-tubular surface treatment) implanted under skin of rats was seen 3 and 6 weeks after implantation, and skin filled at least 30% of available implant space. The duration of implantation, but not implant pore size (in the studied range) or surface treatment statistically influenced skin ingrowth; pore size and time of implantation affected the implant extrusion length (p<0.05). The implant type with the slowest extrusion rate (pore size 40-100 μm) was used in a feline model of prosthetic gait with skin-integrated bone-anchored prosthesis. The developed implantation methods, rehabilitation procedures and feline prostheses allowed 2 animals to utilize skin- and bone-integrated prostheses for dynamically stable locomotion. Prosthetic gait analysis demonstrated that the animals loaded the prosthetic limb, but increased reliance on intact limbs for weight support and propulsion. The obtained results and developed animal model improve the understanding of locomotor stability control and integration of skin with percutaneous implants.

Current physiotherapy practice relies on visual observation of the patient for diagnosis and assessment. The assessment process can potentially be automated to improve accuracy and reliability. This thesis proposes a method to recover patient joint angles and automatically extract movement profiles utilizing small and lightweight body-worn sensors. Joint angles are estimated from sensor measurements via the extended Kalman filter (EKF). Constant-acceleration kinematics is employed as the state evolution model. The forward kinematics of the body is utilized as the measurement model. The state and measurement models are used to estimate the position, velocity and acceleration of each joint, updated based on the sensor inputs from inertial measurement units (IMUs). Additional joint limit constraints are imposed to reduce drift, and an automated approach is developed for estimating and adapting the process noise during on-line estimation. Once joint angles are determined, the exercise data is segmented to identify each of the repetitions. This process of identifying when a particular repetition begins and ends allows the physiotherapist to obtain useful metrics such as the number of repetitions performed, or the time required to complete each repetition. A feature-guided hidden Markov model (HMM) based algorithm is developed for performing the segmentation. In a sequence of unlabelled data, motion segment candidates are found by scanning the data for velocity-based features, such as velocity peaks and zero crossings, which match the pre-determined motion templates. These segment potentials are passed into the HMM for template matching. This two-tier approach combines the speed of a velocity feature based approach, which only requires the data to be differentiated, with the accuracy of the more computationally-heavy HMM, allowing for fast and accurate segmentation. The proposed algorithms were verified experimentally on a dataset consisting of 20 healthy subjects performing rehabilitation exercises. The movement data was collected by IMUs strapped onto the hip, thigh and calf. The joint angle estimation system achieves an overall average RMS error of 4.27 cm, when compared against motion capture data. The segmentation algorithm reports 78% accuracy when the template training data comes from the same participant, and 74% for a generic template.

Today's smartphones are equipped with a variety of different sensors such as GPS receivers, accelerometers, gyroscopes and magnetometers, making smartphones viable tools in many applications. The computational capacity of smartphones allows for software applications running advanced signal processing algorithms. Thus, attaching a smartphone inside a car makes it possible to estimate kinematics of the vehicle by fusing information from the different sensors inside the smartphone. Fusing information from different sources for improving estimation quality is a well-known problem and there exist a lot of methods and algorithms in this area. This thesis approaches the sensor fusion problem of estimating kinematics of cars using smartphones for the purpose of analysing driving performance. Different varieties of the coordinated turn model for describing the vehicle dynamics are investigated. Also, different measurement models are evaluated where bias errors of the sensors are taken into consideration. Pre-filtering and construction of pseudo-measurements are also considered which allow for use of state space models with a lower dimension. / Dagens smartphones är utrustade med en rad olika typer av sensorer såsom GPS mottagare, accelerometrar, gyroskop och magnetometrar vilket medför ett stort användningsområde. Beräkningskapaciteten hos smartphones gör det möjligt för mjukvaruapplikationer att använda sig av avancerade algoritmer för signalbehandling. Det är därför möjligt att placera en smartphone inuti en bil och skatta bilens kinematik genom att kombinera informationen från de olika sensorerna. Att fusionera information från olika källor för att erhålla bättre skattningar är ett välkänt område där det finns många metoder och algoritmer utvecklade. Detta examensarbete behandlar sensorfusionsproblemet att skatta bilars kinematik med hjälp av smartphones för syftet att kunna analysera körprestanda. Olika varianter av en coordinated turn modell för att beskriva bilens dynamik undersöks. Dessutom testas olika modeller för sensorerna där hänsyn till exempelvis biasfel tas. Förbehandling av data och pseudomätningar testas också vilket gör det möjligt att använda tillståndsmodeller med låg dimension.

New surgical approaches for total hip arthroplasty (THA) are being developed to reduce muscle damage sustained during surgery, in the hope to allow better muscle functioning afterwards. The goal of this study was to compare the muscle sparing anterior (ANT) approach to a traditional lateral (LAT) approach with three-dimensional motion analysis. Kinematics and kinetics were obtained with an infrared camera system and force plates. It was hypothesized that (1) the ANT group would have closer to normal range of motion, moments and powers, compared to the LAT group, and that (2) the ANT group would have higher peak hip abduction moment than the LAT group. Forty patients undergoing unilateral THA for osteoarthritis between the ages of 50 and 75 (20 ANT, 20 LAT) were asked to perform three trials of walking, stair ascent and stair descent. Patients were assessed between six to twelve months postoperatively. Twenty age- and weight-matched control participants (CON) provided normative data. Results indicated that both THA groups had gait anomalies compared to the CON group. Both THA groups had reduced hip abduction moment during walking (CON vs. ANT: p<0.001; CON vs. LAT: p=0.011), and the ANT group had a significantly lower hip abduction moment compared to the LAT group (p=0.008). Similar results were observed during stair descent, where the ANT group had reduced peak hip abduction moment compared to the CON group (p<0.001) and the LAT group (p=0.014). This indicates that the anterior approach did not allow better gait and stair climbing ability after THA. It is therefore thought that other variables, such as preoperative gait adaptations, trauma from the surgery, or postoperative protection mechanisms to avoid loading the prosthetic hip, are factors that might be more important than surgical approach in determining the mechanics of THA patients after surgery.

Tai Chi Chuan is a safe alternative for those who wish to improve balance and physical wellbeing. It is a popular form of exercise that is supported by a growing body of research aimed towards improving the health of a sedentary elderly population. The purpose of this study was to examine the biomechanical features of the lower extremity during performance of two Tai Chi movements, the “Repulse Monkey (RM)” and “Wave-hands in clouds (WHIC).” The study’s parameters included quantitative measures of the temporospatial, kinematic, and kinetic characteristics of the lower extremities. A group of experienced male Tai Chi practitioners (n = 15) between the ages of 65 to 75, performed “Repulse Monkey (RM)”, “Wave-hand in Cloud (WHIC)”, and forward walking. Three-dimensional (3-D) kinematic and kinetic data was collected using VICON motion analysis system with 10 infrared cameras and 4 force plates. The following variables were examined: stride width, step length, step width, single- and double-support times, centre of mass (COM) displacement, peak joint angles, range of motion, peak joint moments, time to peak moment, and ground reaction force (GRF). The differences in the measurements of the two Tai Chi movements were compared with walking using two-way ANOVA. The study’s results showed that the two Tai Chi movements elicit gentle and fluid changes to position of the upper body mass and the joints in the lower extremity. In terms of joint kinematics, the knee remained flexed throughout RM and WHIC. Unlike walking, RM had larger abduction and adduction angles at the knee joints and large plantar- and dorsiflexion ROM at the ankle. Reduced posterior, mediolateral, and vertical GRF were seen; the loading joints at the ankle and hip were gentle and smaller than walking. Varus/valgus moments were notably larger at the knee joint during RM and eversion moment was larger at the ankle joint during WHIC movement. A large, but slow loading rate at the knee joint has implication towards the viscoelastic properties of the knee. A better understanding of RM and WHIC would facilitate the improvement of balance, physical capacity, and joint flexibility for the elders.

University of Macau / Faculty of Science and Technology / Department of Electromechanical Engineering

New surgical approaches for total hip arthroplasty (THA) are being developed to reduce muscle damage sustained during surgery, in the hope to allow better muscle functioning afterwards. The goal of this study was to compare the muscle sparing anterior (ANT) approach to a traditional lateral (LAT) approach with three-dimensional motion analysis. Kinematics and kinetics were obtained with an infrared camera system and force plates. It was hypothesized that (1) the ANT group would have closer to normal range of motion, moments and powers, compared to the LAT group, and that (2) the ANT group would have higher peak hip abduction moment than the LAT group. Forty patients undergoing unilateral THA for osteoarthritis between the ages of 50 and 75 (20 ANT, 20 LAT) were asked to perform three trials of walking, stair ascent and stair descent. Patients were assessed between six to twelve months postoperatively. Twenty age- and weight-matched control participants (CON) provided normative data. Results indicated that both THA groups had gait anomalies compared to the CON group. Both THA groups had reduced hip abduction moment during walking (CON vs. ANT: p<0.001; CON vs. LAT: p=0.011), and the ANT group had a significantly lower hip abduction moment compared to the LAT group (p=0.008). Similar results were observed during stair descent, where the ANT group had reduced peak hip abduction moment compared to the CON group (p<0.001) and the LAT group (p=0.014). This indicates that the anterior approach did not allow better gait and stair climbing ability after THA. It is therefore thought that other variables, such as preoperative gait adaptations, trauma from the surgery, or postoperative protection mechanisms to avoid loading the prosthetic hip, are factors that might be more important than surgical approach in determining the mechanics of THA patients after surgery.

Locomotion of animals, whether by running, flying, swimming or crawling, is crucial to their survival. The natural environments they encounter are complex containing fluid, solid or yielding substrates. These environments are often uneven and inclined, which can lead to slipping during footsteps presenting great locomotor challenges. Many animals have specialized appendages for locomotion allowing them to adapt to their environmental conditions. Aquatically adapted animals have fins and flippers to swim through the water, however, some species use their paddle-like appendages to walk on yielding terrestrial substrates like the beach. Beach sand, a granular medium, behaves like a solid or a fluid when stress is applied. Principles of legged locomotion on yielding substrates remain poorly understood, largely due to the lack of fundamental understanding of the complex interactions of body/limbs with these substrates on the level of the Navier-Stokes Equations for fluids. Understanding of the limb-ground interactions of aquatic animals that utilize terrestrial environments can be applied to the ecology and conservation of these species, as well as enhance construction of man-made devices. In this dissertation, we studied the locomotion of hatchling loggerhead sea turtles on granular media integrating biological, robotic, and physics studies to discover principles that govern fin and flipper locomotion on flowing/yielding media. Hatchlings in the field modified their limb use depending on substrate compaction. On soft sand they bent their wrist to utilize the solid features of sand, whereas on hard ground they used a rigid flipper and claw to clasp asperities during forward motion. A sea turtle inspired physical model in the laboratory was used to test detailed kinematics of fin and flipper locomotion on granular media. Coupling of adequate step distance, body lift and thrust generation allowed the robot to move successfully forward avoiding previously disturbed ground. A flat paddle intruder was used to imitate the animal's flipper in physics drag experiments to measure the forces during intrusion and thrust generation.

Robotic automation has been the major driving force in modern industrial developments. High speed pick-and-place operations find their place in many manufacturing applications. The goal of this project is to develop a class of high speed robots that has a planar workspace. The presented robots are intended for pick-and-place applications that have a relatively large workspace. In order to achieve this goal, the robots must be both stiff and light. The design strategies adapted in this study were expanded from the research work by Prof Khajepour and Dr. Behzadipour. The fundamental principles are to utilize a parallel mechanism to enhance robot stiffness and cable construction to reduce moving inertia. A required condition for using cable construction is the ability to hold all cables under tension. This can only be achieved under certain conditions. The design phase of the study includes a static analysis on the robot manipulator that ensures certain mechanical components are always held under tension. This idea is extended to address dynamic situations where the manipulator velocity and acceleration are bounded. Two concept robot configurations, 2D-Deltabot, and 2D-Betabot are presented. Through a series of analyses from the robot inverse kinematic model, the dynamic properties of a robot can be computed in an effective manner. It was determined that the presented robots can achieve 4g acceleration and 4m/s maximum speed within their 700mm by 100mm workspace with a pair of 890W rotary actuators controlling two degrees of freedom. The 2D-Deltabot was chosen for prototype development. A kinematics calibration algorithm was developed to enhance the robot accuracy. Experimental test results had shown that the 2D-Deltabot was capable of running at 81 cycles per minute on a 730mm long pick-and-place path. Further experiments showed that the robot had a position accuracy of 0. 62mm and a position repeatability of 0. 15mm, despite a few manufacturing errors from the prototype fabrication.

Modular and Reconfigurable Robots (MRRs) are those designed to address the increasing demand for flexible and versatile manipulators in manufacturing facilities. The term, modularity, indicates that they are constructed by using a limited number of interchangeable standardized modules which can be assembled in different kinematic configurations. Thereby, a wide variety of specialized robots can be built from a set of standard components. The term, reconfigurability, implies that the robots can be disassembled and rearranged to accommodate different products or tasks rather than being replaced. A set of MRR modules may consist of joints, links, and end-effectors. Different kinematic configurations are achieved by using different joint, link, and end-effector modules and by changing their relative orientation. The number of distinct kinematic configurations, attainable by a set of modules, varies with respect to the size of the module set from several tens to several thousands. Although determining the most suitable configuration for a specific task from a predefined set of modules is a highly nonlinear optimization problem in a hybrid continuous and discrete search space, a solution to this problem is crucial to effectively utilize MRRs in manufacturing facilities. The objective of this thesis is to develop novel optimization methods that can effectively search the Kinematic Configuration (KC) space to identify the most suitable manipulator for any given task. In specific terms, the goal is to develop and synthesize fast and efficient algorithms for a Task-Based Configuration Optimization (TBCO) from a given set of constraints and optimization criteria. To achieve such efficiency, a TBCO solver, based on Memetic Algorithms (MA), is proposed. MAs are hybrids of Genetic Algorithms (GAs) and local search algorithms. MAs benefit from the exploration abilities of GAs and the exploitation abilities of local search methods simultaneously. Consequently, MAs can significantly enhance the search efficiency of a wide range of optimization problems, including the TBCO. To achieve more optimal solutions, the proposed TBCO utilizes all the solutions of the Inverse Kinematics(IK) problem. Another objective is to develop a method for incorporating the multiple solutions of the IK problem in a trajectory optimization framework. The output of the proposed trajectory optimization method consists of a sequence of desired tasks and a single IK solution to reach each task point. Moreover, the total cost of the optimized trajectory is utilized in the TBCO as a performance measure, providing a means to identify kinematic configurations with more efficient optimized trajectories. The final objective is to develop novel IK solvers which are both general and complete. Generality means that the solvers are applicable to all the kinematic configurations which can be assembled from the available module inventory. Completeness entails the algorithm can obtain all the possible IK solutions.