Motion Capture System for Finger Movement Measurement in Parkinson Disease

Parkinson’s disease (PD) is a chronic neurodegenerative disorder that affects almost 1% of the population in the age group above 60 years. The key symptom in PD is the restriction of mobility. The progress of PD is typically documented using the Unified Parkinson’s Disease Rating Scale (UPDRS), which includes a finger-tapping test. We created a measurement tool and a methodology for the objective measurement of the finger-tapping test. We built a contactless three-dimensional (3D) capture system using two cameras and light-passive (wireless) reflexive markers. We proposed and implemented an algorithm for extracting, matching, and tracing markers. The system provides the 3D position of spherical or hemispherical markers in real time. The system’s functionality was verified with the commercial motion capture system OptiTrack. Our motion capture system is easy to use, saves space, is transportable, and needs only a personal computer for data processing—the ideal solution for an outpatient clinic. Its features were successfully tested on 22 patients with PD and 22 healthy control subjects

Evaluation of the Oculus Rift S tracking system in room scale virtual reality

In specific virtual reality applications that require high accuracy it may be advisable to replace the built-in tracking system of the HMD with a third party solution. The purpose of this research work is to evaluate the accuracy of the built-in tracking system of the Oculus Rift S Head Mounted Display (HMD) in room scale environments against a motion capture system. In particular, an experimental evaluation of the Oculus Rift S inside-out tracking technology was carried out, compared to the performance of an outside-in tracking method based on the OptiTrack motion capture system. In order to track the pose of the HMD using the motion capture system the Oculus Rift S was instrumented with passive retro-reflective markers and calibrated. Experiments have been performed on a dataset of multiple paths including simple motions as well as more complex paths. Each recorded path contained simultaneous changes in both position and orientation of the HMD. Our results indicate that in room-scale environments the average translation error for the Oculus Rift S tracking system is about 1.83 cm, and the average rotation error is about 0. 77°, which is 2 orders of magnitude higher than the performance that can be achieved using a motion capture system

Motion capture with Kinect

Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2013, Director: Oriol Pujol VilaMotion capture, motion tracking or mocap are the terms used to describe the process of recording movement and translating that movement onto a digital model, it is used in military, entertainment, sports, and medical application. In film making it refers to recording actions of human actors, and using that information to animate digital character models in 3D animation. Unfortunately, most motion capture systems on today's market are prohibitively expensive for educational institutions and small businesses. My goal is to develop a relatively low-cost competitive motion capture system. So in this research I’m looking for the answer how can create an optical mocap player with a single camera. Current motion capture methods use passive markers that are attached to different body parts of the subject and are therefore intrusive in nature. In applications such as pathological human movement analysis, these markers may introduce an unknown artifact in the motion, and are, in general, cumbersome. So the other key challenge is to produce a system that allows marker-less real-time tracking or near the real time. My ultimate objective is to build a visual system that can integrate the above mentioned components, wherewith can display the user’s movement into an avatar in the virtual space. Finally, I will propose a validation system to validate the user movements. I will evaluate the different postures or complete movements. Moreover, I want to go future and show the result in different ways, such as different viewing angles, different meshes or mesh with illumination

Human-activity-centered measurement system:challenges from laboratory to the real environment in assistive gait wearable robotics

Assistive gait wearable robots (AGWR) have shown a great advancement in developing intelligent devices to assist human in their activities of daily living (ADLs). The rapid technological advancement in sensory technology, actuators, materials and computational intelligence has sped up this development process towards more practical and smart AGWR. However, most assistive gait wearable robots are still confined to be controlled, assessed indoor and within laboratory environments, limiting any potential to provide a real assistance and rehabilitation required to humans in the real environments. The gait assessment parameters play an important role not only in evaluating the patient progress and assistive device performance but also in controlling smart self-adaptable AGWR in real-time. The self-adaptable wearable robots must interactively conform to the changing environments and between users to provide optimal functionality and comfort. This paper discusses the performance parameters, such as comfortability, safety, adaptability, and energy consumption, which are required for the development of an intelligent AGWR for outdoor environments. The challenges to measuring the parameters using current systems for data collection and analysis using vision capture and wearable sensors are presented and discussed

Assessment of Kinematics and Electromyography Following Arthroscopic Single-Tendon Rotator Cuff Repair

Background The increasing demand for rotator cuff (RC) repair patients to return to work as soon as they are physically able has led to exploration of when this is feasible. Current guidelines from our orthopedic surgery clinic recommend a return to work at 9 weeks postoperation. To more fully define capacity to return to work, the current study was conducted using a unique series of quantitative tools. To date, no study has combined 3-dimensional (3D) motion analysis with electromyography (EMG) assessment during activities of daily living (ADLs), including desk tasks, and commonly prescribed rehabilitation exercise. Objective To apply a quantitative, validated upper extremity model to assess the kinematics and muscle activity of the shoulder following repair of the supraspinatus RC tendon compared to that in healthy shoulders. Design A prospective, cross-sectional comparison study. Setting All participants were evaluated during a single session at the Medical College of Wisconsin Department of Orthopaedic Surgery\u27s Motion Analysis Laboratory. Participants Ten participants who were 9-12 weeks post–operative repair of a supraspinatus RC tendon tear and 10 participants with healthy shoulders (HS) were evaluated. Methods All participants were evaluated with 3D motion analysis using a validated upper extremity model and synchronized EMG. Data from the 2 groups were compared using multivariate Hotelling T2 tests with post hoc analyses based on Welch t-tests. Main Outcome Measurements Participants\u27 thoracic and thoracohumeral joint kinematics, temporal-spatial parameters, and RC muscle activity were measured by applying a quantitative upper extremity model during 10 activities of daily living and 3 rehabilitation exercises. These included tasks of hair combing, drinking, writing, computer mouse use, typing, calling, reaching to back pocket, pushing a door open, pulling a door closed, external rotation, internal rotation, and rowing. Results There were significant differences of the thoracohumeral joint motion in only a few of the tested tasks: comb maximal flexion angle (P = .004), pull door internal/external rotation range of motion (P = .020), reach abduction/adduction range of motion (P = .001), reach flexion/extension range of motion (P = .001), reach extension minimal angle (P = .025), active external rotation maximal angle (P = .012), and active external rotation minimal angle (P = .004). The thorax showed significantly different kinematics of maximal flexion angle during the call (P = .011), mouse (P = .007), and drink tasks (P = .005) between the 2 groups. The EMG data analysis showed significantly increased subscapularis activity in the RC repair group during active external rotation. Conclusions Although limited abduction was expected due to repair of the supraspinatus tendon, only a single ADL (reaching to back pocket) had a significantly reduced abduction range of motion. Thoracic motion was shown to be used as a compensatory strategy during seated ADLs. Less flexion of the thorax may create passive shoulder flexion at the thoracohumeral joint in efforts to avoid active flexion. The RC repair group participants were able to accomplish the ADLs within the same time frame and through thoracohumeral joint kinematics similar to those in the healthy shoulder group participants. In summary, this study presents a quantification of the effects of RC repair and rehabilitation on the ability to perform ADLs. It may also point to a need for increased rehabilitation focus on either regaining external rotation strength or range of motion following RC repair to enhance recovery and return to the workforce

Visual Localisation of Mobile Devices in an Indoor Environment under Network Delay Conditions

Current progresses in home automation and service robotic environment have highlighted the need to develop interoperability mechanisms that allow a standard communication between the two systems. During the development of the DHCompliant protocol, the problem of locating mobile devices in an indoor environment has been investigated. The communication of the device with the location service has been carried out to study the time delay that web services offer in front of the sockets. The importance of obtaining data from real-time location systems portends that a basic tool for interoperability, such as web services, can be ineffective in this scenario because of the delays added in the invocation of services. This paper is focused on introducing a web service to resolve a coordinates request without any significant delay in comparison with the sockets