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Proceedings ArticleDOI

Design and testing of lightweight inexpensive motion-capture devices with application to clinical gait analysis

01 Apr 2009-pp 1-7

TL;DR: A low-cost motion capture system that relies on the opensource Player/Stage software development environment, and can be used in conjunction with a socially assistive robotic agent (or a computer interface) for various types of motor task rehabilitation training.

AbstractThe advent of more portable and affordable sensing devices has facilitated the study of rehabilitation robotics. Critical to the further development of therapies and interventions are low-cost, easy-to-use devices that can be applied in clinical and home care settings. In this paper, we present a low-cost motion capture system that relies on the opensource Player/Stage software development environment, and can be used in conjunction with a socially assistive robotic agent (or a computer interface) for various types of motor task rehabilitation training. We describe the hardware and software development for the device, and the activity recognition algorithm we developed to capture the relevant motion data. We present the overall framework in which this system can be adapted to other motor task-based rehabilitation regimens. Finally, we present initial experimental data in the domain of gait rehabilitation, in which we use the system to estimate cadence, walking speed, and stride length.

Topics: Rehabilitation robotics (64%), Motion capture (53%), Software development (51%), Gait (human) (51%)

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Citations
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Journal ArticleDOI
01 Jan 2013
TL;DR: A literature review of several current IMU categories and applications is presented and current methods being used to improve the accuracy of the output from IMU are presented to avoid the errors that latest IMU is facing.
Abstract: Inertial Measurement Unit (IMU) sensors are used widely in many different movable applications. Across many years, the improvements and applications of IMU have increased through various areas such as manufacturing, navigation, and robotics. This paper presents a literature review of several current IMU categories and applications. A few considerations on choosing an IMU for different applications are summarized and current methods being used to improve the accuracy of the output from IMU are also presented to avoid the errors that latest IMU is facing. Improvement methods include the control algorithms and type of filters for the sensor. Pros and cons of the types and algorithms used are also discussed in relation to different applications. 

142 citations


Cites methods from "Design and testing of lightweight i..."

  • ...The fusion was done by Michael Bloesch et al. [18] based on EKF to measure the position of the robot’s leg....

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01 Nov 2004
TL;DR: The design of a modular system for untethered real-time kinematic motion capture using sensors with inertial measuring units (IMU) is described, which is comprised of a set of small and lightweight sensors.
Abstract: We describe the design of a modular system for untethered real-time kinematic motion capture using sensors with inertial measuring units (IMU). Our system is comprised of a set of small and lightweight sensors. Each sensor provides its own global orientation (3 degrees of freedom) and is physically and computationally independent, requiring only external communication. Orientation information from sensors is communicated via wireless to host computer for processing. We present results of the real-time usage of our untethered motion capture system for teleoperating the NASA Robonaut. We also discuss potential applications for untethered motion capture with respect to humanoid robotics.

108 citations


Proceedings ArticleDOI
11 Nov 2010
TL;DR: An approach to wearable sensor-based assessment of motor function in individuals post stroke using a one on-body inertial measurement unit to automate the functional ability (FA) scoring of the Wolf Motor Function Test (WMFT).
Abstract: We present an approach to wearable sensor-based assessment of motor function in individuals post stroke. We make use of one on-body inertial measurement unit (IMU) to automate the functional ability (FA) scoring of the Wolf Motor Function Test (WMFT). WMFT is an assessment instrument used to determine the functional motor capabilities of individuals post stroke. It is comprised of 17 tasks, 15 of which are rated according to performance time and quality of motion. We present signal processing and machine learning tools to estimate the WMFT FA scores of the 15 tasks using IMU data. We treat this as a classification problem in multidimensional feature space and use a supervised learning approach.

50 citations


Proceedings ArticleDOI
22 Mar 2010
TL;DR: A sensing framework and an algorithm to automatically detect total movement time are developed and validated and it is suggested how this framework can be adapted to the remaining WMFT tasks.
Abstract: The advent of new health sensing technologies has presented us with the opportunity to gain richer data from patients undergoing clinical interventions. Such technologies are particularly suited for applications requiring temporal accuracy. The Wolf Motor Function Test (WMFT) is one such application. This assessment is an instrument used to determine functional ability of the paretic and non-paretic limbs in individuals post-stroke. It consists of 17 tasks, 15 of which are scored according to both time and a functional ability scale. We propose a technique that uses wearable sensors and performance sensors to estimate the timing of seven of these tasks. We have developed a sensing framework and an algorithm to automatically detect total movement time. We have validated the system's accuracy on the seven selected WMFT tasks. We also suggest how this framework can be adapted to the remaining tasks.

39 citations


Proceedings ArticleDOI
01 Sep 2010
TL;DR: A SAR architecture is developed that facilitates multiple task-oriented interactions between a user and a robot agent and accommodates a variety of inputs, tasks, and interaction modalities that are used to provide relevant, real-time feedback to the participant.
Abstract: New approaches to rehabilitation and health care have developed due to advances in technology and human robot interaction (HRI). Socially assistive robotics (SAR) is a subcategory of HRI that focuses on providing assistance through hands-off interactions. We have developed a SAR architecture that facilitates multiple task-oriented interactions between a user and a robot agent. The architecture accommodates a variety of inputs, tasks, and interaction modalities that are used to provide relevant, real-time feedback to the participant. We have implemented the architecture and validated its technological feasibility in a small pilot study in which a SAR agent led three post-stroke individuals through an exercise scenario. In the following, we present our architecture design, and the results of the feasibility study.

36 citations


References
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Book
01 Oct 2004
TL;DR: Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts, and discusses many methods from different fields, including statistics, pattern recognition, neural networks, artificial intelligence, signal processing, control, and data mining.
Abstract: The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. In order to present a unified treatment of machine learning problems and solutions, it discusses many methods from different fields, including statistics, pattern recognition, neural networks, artificial intelligence, signal processing, control, and data mining. All learning algorithms are explained so that the student can easily move from the equations in the book to a computer program. The text covers such topics as supervised learning, Bayesian decision theory, parametric methods, multivariate methods, multilayer perceptrons, local models, hidden Markov models, assessing and comparing classification algorithms, and reinforcement learning. New to the second edition are chapters on kernel machines, graphical models, and Bayesian estimation; expanded coverage of statistical tests in a chapter on design and analysis of machine learning experiments; case studies available on the Web (with downloadable results for instructors); and many additional exercises. All chapters have been revised and updated. Introduction to Machine Learning can be used by advanced undergraduates and graduate students who have completed courses in computer programming, probability, calculus, and linear algebra. It will also be of interest to engineers in the field who are concerned with the application of machine learning methods. Adaptive Computation and Machine Learning series

3,947 citations


Proceedings Article
01 Jul 2003
TL;DR: Current usage of Player and Stage is reviewed, and some interesting research opportunities opened up by this infrastructure are identified.
Abstract: This paper describes the Player/Stage software tools applied to multi-robot, distributed-robot and sensor network systems. Player is a robot device server that provides network transparent robot control. Player seeks to constrain controller design as little as possible; it is device independent, non-locking and language- and style-neutral. Stage is a lightweight, highly configurable robot simulator that supports large populations. Player/Stage is a community Free Software project. Current usage of Player and Stage is reviewed, and some interesting research opportunities opened up by this infrastructure are identified.

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Additional excerpts

  • ...We use the Player/Stage software environment [6]....

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Proceedings ArticleDOI
29 Aug 2005
Abstract: This paper defines the research area of socially assistive robotics, focusing on assisting people through social interaction. While much attention has been paid to robots that provide assistance to people through physical contact (which we call contact assistive robotics), and to robots that entertain through social interaction (social interactive robotics), so far there is no clear definition of socially assistive robotics. We summarize active social assistive research projects and classify them by target populations, application domains, and interaction methods. While distinguishing these from socially interactive robotics endeavors, we discuss challenges and opportunities that are specific to the growing field of socially assistive robotics.

721 citations


"Design and testing of lightweight i..." refers background in this paper

  • ...SAR systems assi t through coaching, monitoring, and motivating, but without physical contact [5]....

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  • ...Exploration of this technology has led to developmen ts in wearable health monitoring systems [10], human computer and human robot interactions [8], and in service and assisti ve robotics [5]....

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Journal ArticleDOI
TL;DR: It is concluded that foot inertial sensing is a promising tool for the reliable identification of subsequent gait cycles and the accurate assessment of walking speed and incline.
Abstract: An ambulatory monitoring system is developed for the estimation of spatio-temporal gait parameters. The inertial measurement unit embedded in the system is composed of one biaxial accelerometer and one rate gyroscope, and it reconstructs the sagittal trajectory of a sensed point on the instep of the foot. A gait phase segmentation procedure is devised to determine temporal gait parameters, including stride time and relative stance; the procedure allows to define the time intervals needed for carrying an efficient implementation of the strapdown integration, which allows to estimate stride length, walking speed, and incline. The measurement accuracy of walking speed and inclines assessments is evaluated by experiments carried on adult healthy subjects walking on a motorized treadmill. Root-mean-square errors less than 0.18 km/h (speed) and 1.52% (incline) are obtained for tested speeds and inclines varying in the intervals [3, 6] km/h and [-5, +15]%, respectively. Based on the results of these experiments, it is concluded that foot inertial sensing is a promising tool for the reliable identification of subsequent gait cycles and the accurate assessment of walking speed and incline.

596 citations


"Design and testing of lightweight i..." refers result in this paper

  • ...) When comparing these results to those obtained from other inertial sensors used for gait, we get similarly accurate results, but with the advantage of be ing able to place our IMU on the ankle, out of the way of any footwear [12]....

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Journal ArticleDOI
TL;DR: The method provides a simple yet effective way of ambulatory gait analysis in PD patients with results confirming those obtained from much more complex and expensive methods used in gait labs.
Abstract: An ambulatory gait analysis method using body-attached gyroscopes to estimate spatio-temporal parameters of gait has been proposed and validated against a reference system for normal and pathologic gait. Later, ten Parkinson's disease (PD) patients with subthalamic nucleus deep brain stimulation (STN-DBS) implantation participated in gait measurements using our device. They walked one to three times on a 20-m walkway. Patients did the test twice: once STN-DBS was ON and once 180 min after turning it OFF. A group of ten age-matched normal subjects were also measured as controls. For each gait cycle, spatio-temporal parameters such as stride length (SL), stride velocity (SV), stance (ST), double support (DS), and gait cycle time (GC) were calculated. We found that PD patients had significantly different gait parameters comparing to controls. They had 52% less SV, 60% less SL, and 40% longer GC. Also they had significantly longer ST and DS (11% and 59% more, respectively) than controls. STN-DBS significantly improved gait parameters. During the stim ON period, PD patients had 31% faster SV, 26% longer SL, 6% shorter ST, and 26% shorter DS. GC, however, was not significantly different. Some of the gait parameters had high correlation with Unified Parkinson's Disease Rating Scale (UPDRS) subscores including SL with a significant correlation (r=-0.90) with UPDRS gait subscore. We concluded that our method provides a simple yet effective way of ambulatory gait analysis in PD patients with results confirming those obtained from much more complex and expensive methods used in gait labs.

547 citations


"Design and testing of lightweight i..." refers background in this paper

  • ...It was shown by [13] that inertial measurement units (IMUs) consisting of accelerometers and rate gyros can be used to accurately estimate values for these characteristics....

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