Ruzena Bajcsy | University of California, Berkeley (original) (raw)
Papers by Ruzena Bajcsy
Engineering Systems with Intelligence, 1991
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Neuromuscular Disorders, 2013
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Autonomous Robots, 2017
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Nature, 2006
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International Journal of Computer Vision, 1996
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2010 IEEE International Conference on Multimedia and Expo, 2010
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International Journal of Computer Vision, 1995
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Studies in health technology and informatics, 2013
We present mobile health (mHealth) applications utilizing embedded phone sensors as an angle-meas... more We present mobile health (mHealth) applications utilizing embedded phone sensors as an angle-measuring device for upper-limb range of motion (ROM) and estimation of reachable workspace to assist in evaluation of upper limb functional capacity. Our results show that the phone can record accurate measurements, as well as provide additional functionalities for clinicians.
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Studies in health technology and informatics, 2013
We propose a novel low-cost method for quantitative assessment of upper extremity workspace envel... more We propose a novel low-cost method for quantitative assessment of upper extremity workspace envelope using Microsoft Kinect camera. In clinical environment there are currently no practical and cost-effective methods available to provide arm-function evaluation in three-dimensional space. In this paper we examine the accuracy of the proposed technique for workspace estimation using Kinect in comparison with a motion capture system. The experimental results show that the developed system is capable of capturing the workspace with sufficient accuracy and robustness.
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Studies in health technology and informatics, 2012
We present a real-time algorithm for human pose detection and tracking from vision-based 3D data ... more We present a real-time algorithm for human pose detection and tracking from vision-based 3D data and its application to tele-rehabilitation in virtual environments. We employ stereo camera(s) to capture 3D avatars of geographically dislocated patient and therapist in real-time, while sending the data remotely and displaying it in a virtual scene. A pose detection and tracking algorithm extracts kinematic parameters from each participant and determines pose similarity. The pose similarity score is used to quantify patient's performance and provide real-time feedback for remote rehabilitation.
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2012 American Control Conference (ACC), 2012
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2015 International Conference on Healthcare Informatics, 2015
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Studies in health technology and informatics
We present work-in-progress on framework for 3D Kinect-based remote motion and function assessmen... more We present work-in-progress on framework for 3D Kinect-based remote motion and function assessment. Tele-MFAsT facilities streaming of data (video, depth, skeleton, and audio) from network-connected Microsoft Kinect cameras that can be utilized to observe a patient remotely during function assessment by a physician or therapist, measure motion trajectories, and joint angles, while taking advantage of tele-presence in a 3D virtual environment. The network architecture also allows for integration with wireless sensors in the future. In this paper we describe Tele-MFAsT application for upper-body range of motion measurements.
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2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2013
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Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments - PETRA '10, 2010
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2011 IEEE Fifth International Conference on Semantic Computing, 2011
ABSTRACT Within context-aware computing, there is a growing interest in linking localization tech... more ABSTRACT Within context-aware computing, there is a growing interest in linking localization technologies with activity recognition in a cooperative way. Existing research works in this field face two main difficulties: lack of accuracy in their solutions and/or sophisticated hardware requirements. To avoid these issues, we present a light-weight, low-cost and high-accuracy system for localization and activity recognition, based on a smart phone and a single off-the-shelf wireless accelerometer attached to the waist. We process the accelerometer signal with the wavelet transform to precisely recognize different activities and obtain the velocity of the gait in real time. Additionally, we leverage the capabilities of the smart phone to accurately estimate locations making use of a multimode approach for radio fingerprinting. Eventually, we combine location information with activity recognition, observing a 9% improvement in the accuracy with which some activities are recognized.
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Engineering Systems with Intelligence, 1991
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Neuromuscular Disorders, 2013
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Autonomous Robots, 2017
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Nature, 2006
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International Journal of Computer Vision, 1996
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2010 IEEE International Conference on Multimedia and Expo, 2010
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International Journal of Computer Vision, 1995
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Studies in health technology and informatics, 2013
We present mobile health (mHealth) applications utilizing embedded phone sensors as an angle-meas... more We present mobile health (mHealth) applications utilizing embedded phone sensors as an angle-measuring device for upper-limb range of motion (ROM) and estimation of reachable workspace to assist in evaluation of upper limb functional capacity. Our results show that the phone can record accurate measurements, as well as provide additional functionalities for clinicians.
Bookmarks Related papers MentionsView impact
Studies in health technology and informatics, 2013
We propose a novel low-cost method for quantitative assessment of upper extremity workspace envel... more We propose a novel low-cost method for quantitative assessment of upper extremity workspace envelope using Microsoft Kinect camera. In clinical environment there are currently no practical and cost-effective methods available to provide arm-function evaluation in three-dimensional space. In this paper we examine the accuracy of the proposed technique for workspace estimation using Kinect in comparison with a motion capture system. The experimental results show that the developed system is capable of capturing the workspace with sufficient accuracy and robustness.
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Studies in health technology and informatics, 2012
We present a real-time algorithm for human pose detection and tracking from vision-based 3D data ... more We present a real-time algorithm for human pose detection and tracking from vision-based 3D data and its application to tele-rehabilitation in virtual environments. We employ stereo camera(s) to capture 3D avatars of geographically dislocated patient and therapist in real-time, while sending the data remotely and displaying it in a virtual scene. A pose detection and tracking algorithm extracts kinematic parameters from each participant and determines pose similarity. The pose similarity score is used to quantify patient's performance and provide real-time feedback for remote rehabilitation.
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2012 American Control Conference (ACC), 2012
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2015 International Conference on Healthcare Informatics, 2015
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Studies in health technology and informatics
We present work-in-progress on framework for 3D Kinect-based remote motion and function assessmen... more We present work-in-progress on framework for 3D Kinect-based remote motion and function assessment. Tele-MFAsT facilities streaming of data (video, depth, skeleton, and audio) from network-connected Microsoft Kinect cameras that can be utilized to observe a patient remotely during function assessment by a physician or therapist, measure motion trajectories, and joint angles, while taking advantage of tele-presence in a 3D virtual environment. The network architecture also allows for integration with wireless sensors in the future. In this paper we describe Tele-MFAsT application for upper-body range of motion measurements.
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2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2013
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Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments - PETRA '10, 2010
Bookmarks Related papers MentionsView impact
2011 IEEE Fifth International Conference on Semantic Computing, 2011
ABSTRACT Within context-aware computing, there is a growing interest in linking localization tech... more ABSTRACT Within context-aware computing, there is a growing interest in linking localization technologies with activity recognition in a cooperative way. Existing research works in this field face two main difficulties: lack of accuracy in their solutions and/or sophisticated hardware requirements. To avoid these issues, we present a light-weight, low-cost and high-accuracy system for localization and activity recognition, based on a smart phone and a single off-the-shelf wireless accelerometer attached to the waist. We process the accelerometer signal with the wavelet transform to precisely recognize different activities and obtain the velocity of the gait in real time. Additionally, we leverage the capabilities of the smart phone to accurately estimate locations making use of a multimode approach for radio fingerprinting. Eventually, we combine location information with activity recognition, observing a 9% improvement in the accuracy with which some activities are recognized.
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In this work we establish a framework for the general problem of observation, which may be applie... more In this work we establish a framework for the general problem of observation, which may be applied to different kinds of visual tasks. We construct ‘intelligent’ high-level control mechanisms for active visual recognition of different processes within a hybrid dynamic system. We address the problem of observing a manipulation process in order to illustrate the ideas and motive behind our framework. We use a discrete event dynamic system as a high-level structuring technique to model the manipulation system. The formulation utilizes the knowledge about the system and the different actions in order to solve the observer problem in an efficient, stable and practical manner. The model uses different tracking mechanisms so that the observer can ‘see’ the workspace of the manipulating robot. An automaton is developed for the hand/object interaction over time and a stabilizing observer is constructed. Low-level modules are developed for recognizing the visual ‘events’ that causes state transitions within the dynamic manipulation system in real time. A coarse quantization of the manipulation actions is used in order to attain an active, adaptive and goaldirected sensing mechanism. The formulation provides high-level symbolic interpretations of the scene under observation. The discrete event framework is augmented with mechanisms for recovering the continuous parametric evolution of the scene under observation and for asserting the state of the manipulation agent. This work examines closely the possibilities for errors, mistakes and uncertainties in the manipulation system, observer construction process and event identification mechanisms. We identify and suggest techniques for modeling these uncertainties. Ambiguities are allowed to develop and are resolved after finite time. Error recovery mechanisms are also devised. The computed uncertainties are utilized for navigating the observer automaton state space, asserting state transitions and developing a suitable tracking
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