Ceiling-mounted Camera Research Articles

0065 A Novel Automated Task for Spatial Learning in Rodents

Abstract Introduction Spatial learning in rodents is useful for addressing a variety of research questions. We set out to create a fully automated spatial learning task that required rodents to make a sequence of cued navigational decisions. We used this maze to investigate the impact of sleep on insight gain, a sudden rather than gradual acquisition of a skill or behavior. Methods We designed a circular four-quadrant elevated maze. Each quadrant had three choice points on a branched arm, consisting of a reward well and cue light. To discourage rats from backtracking, motorized doors were placed between quadrants. Rats were trained to follow the light for a water reward. Their position was tracked by custom MATLAB code processing live video from a ceiling-mounted camera; the code also controlled all components of the maze, calculated and presented novel routes through the maze, analyzed results in real time, and maintained records of each rat across sessions. After an average of five days rats reached criterion in pretraining (following lights in pseudorandom positions) and were taught a hidden rule: the direction cued on the second quadrant was the correct direction on the fourth (uncued) quadrant. Rats completed one session each in the morning and afternoon, separated by 3h of sleep opportunity or sleep disruption, achieved by gentle handling. This was repeated after a night of sleep opportunity or sleep disruption for a total of four sessions. Results Rats quickly learned and consistently chose the correct well, remaining motivated for 96 consecutive trials. Rats were said to have gained insight if they demonstrated significant learning of the hidden rule. Although no animals have yet met this criterion, there was a trend of sleep-disrupted rats performing worse, suggesting that sleep plays an important role in consolidating the spatial rules of the task. Conclusion The versatility of this maze can accommodate many tasks not limited to insight gain specifically. Delivering rewards consistently at multiple distinct locations is a valuable technique for investigating spatial learning, navigation, and decision making, making this maze a powerful tool for investigating interventions for disease models that implicate the hippocampus or striatum. Support (if any)

What children with and without ASD see: Similar visual experiences with different pathways through parental attention strategies.

Although young children's gaze behaviors in experimental task contexts have been shown to be potential biobehavioral markers relevant to autism spectrum disorder (ASD), we know little about their everyday gaze behaviors. The present study aims (1) to document early gaze behaviors that occur within a live, social interactive context among children with and without ASD and their parents, and (2) to examine how children's and parents' gaze behaviors are related for ASD and typically developing (TD) groups. A head-mounted eye-tracking system was used to record the frequency and duration of a set of gaze behaviors (such as sustained attention [SA] and joint attention [JA]) that are relevant to early cognitive and language development. Twenty-six parent-child dyads (ASD group = 13, TD group = 13) participated. Children were between the ages of 3 and 8 years old. We placed head-mounted eye trackers on parents and children to record their parent- and child-centered views, and we also recorded their interactive parent-child object play scene from both a wall- and ceiling-mounted camera. We then annotated the frequency and duration of gaze behaviors (saccades, fixation, SA, and JA) for different regions of interest (object, face, and hands), and attention shifting. Independent group t-tests and ANOVAs were used to observe group comparisons, and linear regression was used to test the predictiveness of parent gaze behaviors for JA. The present study found no differences in visual experiences between children with and without ASD. Interestingly, however, significant group differences were found for parent gaze behaviors. Compared to parents of ASD children, parents of TD children focused on objects and shifted their attention between objects and their children's faces more. In contrast, parents of ASD children were more likely to shift their attention between their own hands and their children. JA experiences were also predicted differently, depending on the group: among parents of TD children, attention to objects predicted JA, but among parents of ASD children, attention to their children predicted JA. Although no differences were found between gaze behaviors of autistic and TD children in this study, there were significant group differences in parents' looking behaviors. This suggests potentially differential pathways for the scaffolding effect of parental gaze for ASD children compared with TD children. The present study revealed the impact of everyday life, social interactive context on early visual experiences, and point to potentially different pathways by which parental looking behaviors guide the looking behaviors of children with and without ASD. Identifying parental social input relevant to early attention development (e.g., JA) among autistic children has implications for mechanisms that could support socially mediated attention behaviors that have been documented to facilitate early cognitive and language development and implications for the development of parent-mediated interventions for young children with or at risk for ASD.Note: This paper uses a combination of person-first and identity-first language, an intentional decision aligning with comments put forth by Vivanti (Vivanti, 2020), recognizing the complexities of known and unknown preferences of those in the larger autism community.

Fuzzy Integral Sliding Mode Observer-Based Formation Control of Mobile Robots With Kinematic Disturbance and Unknown Leader and Follower Velocities

Fuzzy integral sliding mode observer (FISMO) based leader-follower formation control with the use of ceiling-mounted camera information is proposed for mobile robots with kinematic disturbance and no information of the velocities of leader and follower robots. Using only the posture information of both the leader and follower robots obtained from the camera sensor, the follower robot is made to follow the trajectory of a target robot that is introduced to render the leader-follower formation control more efficient. As a result, a kinematic tracking error model is proposed in terms of both the posture error between the target and follower robots and the posture error between the origin of the inertial reference frame and follower robot. Because the kinematic disturbance and the velocities of the leader and follower robots are not available, an FISMO is designed to simultaneously estimate the kinematic disturbance as well as the linear and angular velocities of the leader and follower robots. FISMO-based leader-follower output feedback formation control is then proposed based on the estimates of the kinematic disturbance and velocities and the backstepping-like feedback linearization tracking control. The experimental results comparing the proposed FISMO-based method with the robust distance-based tracking control method and integral sliding mode observer (ISMO)-based method are provided to verify the effectiveness of the proposed method.

Adaptive Visually Servoed Tracking Control for Wheeled Mobile Robot with Uncertain Model Parameters in Complex Environment

This paper investigates the stabilization and trajectory tracking problem of wheeled mobile robot with a ceiling-mounted camera in complex environment. First, an adaptive visual servoing controller is proposed based on the uncalibrated kinematic model due to the complex operation environment. Then, an adaptive controller is derived to provide a solution of uncertain dynamic control for a wheeled mobile robot subject to parametric uncertainties. Furthermore, the proposed controllers can be applied to a more general situation where the parallelism requirement between the image plane and operation plane is no more needed. The overparameterization of regressor matrices is avoided by exploring the structure of the camera-robot system, and thus, the computational complexity of the controller can be simplified. The Lyapunov method is employed to testify the stability of a closed-loop system. Finally, simulation results are presented to demonstrate the performance of the suggested control.

Protection of Dialysis Staff From COVID-19 Infection: Setting Up and Impact of Extended Blood Lines During Dialysis.

Protection of Dialysis Staff From COVID-19 Infection: Setting Up and Impact of Extended Blood Lines During Dialysis.

Accuracy of Broiler Activity Index as Affected by Sampling Time Interval.

Simple SummaryBroiler activity index is a measure of bird movement through determining bird-representative pixel changes between consecutive images. Since the concept of activity index was coined, different sampling time intervals of consecutive images have been used to determine broiler activity. In this study, we found that accuracy of broiler activity decreased at longer sampling time intervals, with the 0.04-s interval yielding the most accurate activity index among all intervals investigated. In addition, broiler activity in the commercial house generally decreased as birds aged and varied at different monitoring locations. The research provides insights into image-sampling strategies for accurately determining broiler activity index, which may help to address growing public concerns on poultry welfare and health. Different time intervals between consecutive images have been used to determine broiler activity index (AI). However, the accuracy of broiler AI as affected by sampling time interval remains to be explored. The objective of this study was to investigate the effect of the sampling time interval (0.04, 0.2, 1, 10, 60, and 300 s) on the accuracy of broiler AI at different bird ages (1–7 weeks), locations (feeder, drinker, and open areas) and times of day (06:00–07:00 h, 12:00–13:00 h, and 18:00–19:00 h). A ceiling-mounted camera was used to capture top-view videos for broiler AI calculations. The results show that the sampling time interval of 0.04 s yielded the highest broiler AI because more bird motion details were captured at this short time interval. The broiler AIs at longer time intervals were 1–99% of that determined at the 0.04-s interval. The broiler AI at 0.2-s interval showed an acceptable accuracy with 80% less computational resources. Broiler AI decreased as birds aged but increased after week 4 at the drinker area. Broiler AI was the highest at the open area for weeks 1–4 and at the feeder and drinker areas for weeks 5–7. It is concluded that the accuracy of broiler AI was significantly affected by sampling time intervals. Broiler AI in commercial housing showed both temporal and spatial variations.

A Novel Approach to Assess Sleep-Related Rhythmic Movement Disorder in Children Using Automatic 3D Analysis.

Background: Unlike other episodic sleep disorders in childhood, there are no agreed severity indices for rhythmic movement disorder. While movements can be characterized in detail by polysomnography, in our experience most children inhibit rhythmic movement during polysomnography. Actigraphy and home video allow assessment in the child’s own environment, but both have limitations. Standard actigraphy analysis algorithms fail to differentiate rhythmic movements from other movements. Manual annotation of 2D video is time consuming. We aimed to develop a sensitive, reliable method to detect and quantify rhythmic movements using marker free and automatic 3D video analysis. Method: Patients with rhythmic movement disorder (n = 6, 4 male) between age 5 and 14 years (M: 9.0 years, SD: 4.2 years) spent three nights in the sleep laboratory as part of a feasibility study (https://clinicaltrials.gov/ct2/show/NCT03528096). 2D and 3D video data recorded during the adaptation and baseline nights were analyzed. One ceiling-mounted camera captured 3D depth images, while another recorded 2D video. We developed algorithms to analyze the characteristics of rhythmic movements and built a classifier to distinguish between rhythmic and non-rhythmic movements based on 3D video data alone. Data from 3D automated analysis were compared to manual 2D video annotations to assess algorithm performance. Novel indices were developed, specifically the rhythmic movement index, frequency index, and duration index, to better characterize severity of rhythmic movement disorder in children. Result: Automatic 3D video analysis demonstrated high levels of agreement with the manual approach indicated by a Cohen’s kappa >0.9 and F1-score >0.9. We also demonstrated how rhythmic movement assessment can be improved using newly introduced indices illustrated with plots for ease of visualization. Conclusion: 3D video technology is widely available and can be readily integrated into sleep laboratory settings. Our automatic 3D video analysis algorithm yields reliable quantitative information about rhythmic movements, reducing the burden of manual scoring. Furthermore, we propose novel rhythmic movement disorder severity indices that offer a means to standardize measurement of this disorder in both clinical and research practice. The significance of the results is limited due to the nature of a feasibility study and its small number of samples. A larger follow up study is needed to confirm presented results.

Calibration of mobile-gantry computed tomography for surgical navigation.

Image-guided interventions that use preoperative 3D computed tomography (CT) models are limited by the preoperative segmentation time 3D image and collection of intraoperative registration data. Intraoperative CT imaging can be ergonomically efficient in a direct navigation system if the imaging device is accurately calibrated. A mobile-gantry CT scanner offers improved patient safety but presents technical challenges beyond those of a conventional scanner. The goal was to calibrate an optoelectronic navigation system to mobile-gantry CT with millimeter-level accuracy. A custom calibration device was designed and manufactured. The calibrator contained optoelectronic markers for navigation reference and radio-opaque markers for CT reference. Calibrations were performed with a ceiling-mounted optoelectronic camera and with a portable camera, and then verified for accuracy. The component fiducial registration errors were extremely small, being 0.36 mm, with standard deviation of 0.16 mm, for the ceiling-mounted camera, and 0.05 mm, with standard deviation of 0.01 mm, for the portable camera. The net target registration error, measured as RMS deviation, was 1.58 mm for the ceiling-mounted camera and 0.73 mm for the portable camera. High-accuracy calibration of the mobile-gantry CT scanner was possible from a single preoperative CT image. A ceiling-mounted optoelectronic camera, which is ergonomically preferable, marginally met the accuracy criteria. The portable camera, which is in widespread use for conventional navigated surgery, had deep sub-millimeter error. This study demonstrates that high accuracy is achievable and offers a system developer options to trade off accuracy and user convenience in direct surgical navigation.

Learning indoor robot navigation using visual and sensorimotor map information

As a fundamental research topic, autonomous indoor robot navigation continues to be a challenge in unconstrained real-world indoor environments. Although many models for map-building and planning exist, it is difficult to integrate them due to the high amount of noise, dynamics, and complexity. Addressing this challenge, this paper describes a neural model for environment mapping and robot navigation based on learning spatial knowledge. Considering that a person typically moves within a room without colliding with objects, this model learns the spatial knowledge by observing the person's movement using a ceiling-mounted camera. A robot can plan and navigate to any given position in the room based on the acquired map, and adapt it based on having identified possible obstacles. In addition, salient visual features are learned and stored in the map during navigation. This anchoring of visual features in the map enables the robot to find and navigate to a target object by showing an image of it. We implement this model on a humanoid robot and tests are conducted in a home-like environment. Results of our experiments show that the learned sensorimotor map masters complex navigation tasks.

Path Tracking Controller of Quadruped Robot for Obstacle Avoidance Using Potential Functions Method

This paper proposes a tracking controller for obstacle avoidance of a quadruped robot using potential functions method. The followings are done for this task. At first, a ceiling-mounted camera system is installed for image processing. The goal point and obstacles are separated and recognized by a color recognition method. Second, a path planning algorithm using potential functions method is proposed to generate the path to avoid obstacles and to plan a path for the quadruped robot to reach from start point to goal point. Third, a quadruped robot is chosen as the mobile platform for this study and the kinematic model for the robot is presented. Fourth, a tracking controller is designed for the quadruped robot to track the trajectory based on the backstepping method using Lyapunov function. Finally, the simulation results are presented to show the effectiveness of the proposed trajectory planning algorithm and the tracking controller. [Keywords — Path tracking ; back stepping ; obstacles avoidance ; potential functions ; quadruped robot ] .

A hybrid probabilistic neural model for person tracking based on a ceiling-mounted camera

Person tracking is an important topic in ambient living systems as well as in computer vision. In particular, detecting a person from a ceiling-mounted camera is a challenge since the person's appe...

Motion monitoring for cranial frameless stereotactic radiosurgery using video‐based three‐dimensional optical surface imaging

To establish a new clinical procedure in frameless stereotactic radiosurgery (SRS) for patient setup verification at treatment couch angles as well as for head-motion monitoring during treatment using video-based optical surface imaging (OSI). A video-based three-dimensional (3D) OSI system with three ceiling-mounted camera pods was employed to verify setup at treatment couch angles as well as to monitor head motion during treatment. A noninvasive head immobilization device was utilized, which includes an alpha head mold and a dental mouthpiece with vacuum suction; both were locked to the treatment couch. Cone beam computed tomography (CBCT) was used as the standard for image-guided setup. Orthogonal 2D-kV imaging was applied for setup verification before treatment, between couch rotations, and after treatment at zero couch angle. At various treatment couch angles, OSI setup verification was performed, relative to initial OSI setup verification at zero couch angle after CBCT setup through a coordinate transformation. For motion monitoring, the setup uncertainty was decoupled by taking an on-site surface image as new reference to detect motion-induced misalignment in near real-time (1-2 frames per second). Initial thermal instability baseline of the real-time monitoring was corrected. An anthropomorphous head phantom and a 1D positioning platform were used to assess the OSI accuracy in motion detection in longitudinal and lateral directions. Two hypofractionated (9 Gy x 3 and 6 Gy x 5) frameless stereotactic radiotherapy (SRT) patients as well as two single-fraction (21 and 18 Gy) frameless SRS patients were treated using this frameless procedure. For comparison, 11 conventional frame-based SRS patients were monitored using the OSI to serve as clinical standards. Multiple noncoplanar conformal beams were used for planning both frameless and frame-based SRS with a micromultileaf collimator. The accuracy of the OSI in 1D motion detection was found to be 0.1 mm with uncertainty of +/- 0.1 mm using the head phantom. The OSI registration against simulation computed tomography (CT) external contour was found to be dependent on the CT skin definition with -0.4 mm variation. For frame-based SRS patients, head-motion magnitude was detected to be <1.0 mm (0.3 +/- 0.2 mm) and <1.0 degree (0.2 degrees +/- 0.2 degrees) for 98% of treatment time, with exception of one patient with head rotation <1.5 degrees for 98% of the time. For frameless SRT/SRS patients, similar motion magnitudes were observed with an average of 0.3 +/- 0.2 mm and 0.2 degrees +/- 0.1 degree in ten treatments. For 98% of the time, the motion magnitude was <1.1 mm and 1.0 degree. Complex head-motion patterns within 1.0 mm were observed for frameless SRT/SRS patients. The OSI setup verification at treatment couch angles was found to be within 1.0 mm. The OSI system is capable of detecting 0.1 +/- 0.1 mm 1D spatial displacement of a phantom in near real time and useful in head-motion monitoring. This new frameless SRS procedure using the mask-less head-fixation system provides immobilization similar to that of conventional frame-based SRS. Head-motion monitoring using near-real-time surface imaging provides adequate accuracy and is necessary for frameless SRS in case of unexpected head motion that exceeds a set tolerance.

A hybrid probabilistic neural model for person tracking based on a ceiling-mounted camera

Person tracking is an important topic in ambient living systems as well as in computer vision. In particular, detecting a person from a ceiling-mounted camera is a challenge since the person's appearance is very different from the top or from the side view, and the shape of the person changes significantly when moving around the room. This article presents a novel approach for a real-time person tracking system based on particle filters with input from different visual streams. A new architecture is developed that integrates different vision streams by means of a Sigma-Pi-like network. Moreover, a short-term memory mechanism is modeled to enhance the robustness of the tracking system. Based on this architecture, the system can start localizing a person with several cues and learn the features of other cues online. The experimental results show that robust real-time person tracking can be achieved.

Design and development of a new facility for teaching and research in clinical anatomy

This article discusses factors in the design, commissioning, project management, and intellectual property protection of developments within a new clinical anatomy facility in the United Kingdom. The project was aimed at creating cost-effective facilities that would address widespread concerns over anatomy teaching, and support other activities central to the university mission-namely research and community interaction. The new facilities comprise an engaging learning environment and were designed to support a range of pedagogies appropriate to the needs of healthcare professionals at different stages of their careers. Specific innovations include integrated workstations each comprising of a dissection table, with removable top sections, an overhead operating light, and ceiling-mounted camera. The tables incorporate waterproof touch-screen monitors to display images from the camera, an endoscope or a database of images, videos, and tutorials. The screens work independently so that instructors can run different teaching sessions simultaneously and students can progress at different speeds to suit themselves. Further, database access is provided from within an integrated anatomy and pathology museum and display units dedicated to the correlation of cross-sectional anatomy with medical imaging. A new functional neuroanatomy modeling system, called the BrainTower, has been developed to aid integration of anatomy with physiology and clinical neurology. Many aspects of the new facility are reproduced within a Mobile Teaching Unit, which can be driven to hospitals, colleges, and schools to provide appropriate work-based education and community interaction.

Perception of eye contact in video teleconsultation

During patient consultations by videoconferencing, clinicians often sit as close as 1 m from the videoconferencing units, creating a significant eye gaze angle (i.e. the angle between the eye and the camera, and the eye and the centre of the display). Eye gaze angle may adversely affect the satisfaction with videoconferencing. Four videoconferencing environments were examined: desktop PC, portable telehealth unit, videoconferencing room, and a boardroom equipped with a ceiling-mounted camera and a projection screen. Two still images of each of the three subjects were captured: one at a 7 degrees eye gaze angle and the other at 15 degrees. Each of 53 observers ranked four pairs of images for each of the three subjects. In 87% of cases, the observers perceived better eye contact at an eye gaze angle of 7 degrees than 15 degrees. Also, 92% of observers responded that the difference in the perceived eye contact was important to them as patients. Improved eye contact can be realized by increasing the horizontal distance of participants from the videoconferencing unit.