Relevant bibliographies by topics / Hands-free control

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Hands-free control'

Author: Grafiati
Published: 4 June 2021
Last updated: 2 February 2022

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Journal articles on the topic "Hands-free control"

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Antony, Pooja, and Sunny Joseph. "Hands free computer control." International Journal on Cybernetics & Informatics 5, no. 2 (2016): 329–38. http://dx.doi.org/10.5121/ijci.2016.5235.

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Breining, Christina. "Control of a hands-free telephone set." Signal Processing 61, no. 2 (1997): 131–43. http://dx.doi.org/10.1016/s0165-1684(97)00098-4.

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Flanagan, J. L., D. A. Berkley, and K. L. Shipley. "Hands‐free voice control of teleconferencing systems." Journal of the Acoustical Society of America 88, S1 (1990): S115. http://dx.doi.org/10.1121/1.2028530.

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Calhoun, Gloria, Scott Grigsby, and Nick LaDue. "Integrated, Hands-Free Control Suite for Wearable Computers." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 45, no. 8 (2001): 750. http://dx.doi.org/10.1177/154193120104500805.

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Nam, Miyoung, Minhaz Uddin Ahmed, Yan Shen, and Phill Kyu Rhee. "Mouth tracking for hands-free robot control systems." International Journal of Control, Automation and Systems 12, no. 3 (2014): 628–36. http://dx.doi.org/10.1007/s12555-012-0473-7.

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De Laurentis, Kathryn J., and Matthew Wills. "DESIGN OF AN ELECTROMECHANICAL HANDS-FREE CONTROL USER INTERFACE." Technology & Innovation 14, no. 3 (2012): 341–49. http://dx.doi.org/10.3727/194982412x13500042169135.

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ZHANG, Yi, Xiang ZHU, Ling-ling DAI, and Yuan LUO. "Forehead sEMG signal based HMI for hands-free control." Journal of China Universities of Posts and Telecommunications 21, no. 3 (2014): 98–105. http://dx.doi.org/10.1016/s1005-8885(14)60306-x.

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Simpson, T., C. Broughton, M. J. A. Gauthier, and A. Prochazka. "Tooth-Click Control of a Hands-Free Computer Interface." IEEE Transactions on Biomedical Engineering 55, no. 8 (2008): 2050–56. http://dx.doi.org/10.1109/tbme.2008.921161.

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Ashok, Sharmila. "High-level hands-free control of wheelchair – a review." Journal of Medical Engineering & Technology 41, no. 1 (2016): 46–64. http://dx.doi.org/10.1080/03091902.2016.1210685.

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Hänsler, Eberhard, and Gerhard Uwe Schmidt. "Hands-free telephones – joint control of echo cancellation and postfiltering." Signal Processing 80, no. 11 (2000): 2295–305. http://dx.doi.org/10.1016/s0165-1684(00)00118-3.

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Dissertations / Theses on the topic "Hands-free control"

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Draghici, Ovidiu. "The MouthPad - a Tongue Interface for Hands-Free Computer Control." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31855.

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Tongue-computer interfaces allow people with upper limb disability to control a computer with their tongue. A number of assistive devices, that make use of this technology, have been developed in the last two decades: some employ contact impedance, membrane switches, or miniature joysticks, while others use magnetic or piezoelectric sensors. This thesis proposes a new tongue-computer interface, which was designed to enable users to manipulate a computer pointer by moving the tip of their tongue over an intraoral electrode array. The system maps the contact between the tongue and the electrodes, detects the movements of the tongue, and translates it into pointer movements. Compared to similar devices, the MouthPad does not require any head gear or sensors, and does not employ heavy signal processing. The hardware is simplified by using a small number of electrodes and only one output channel, multiplexed over the electrode array. A low power footprint allows the potential miniaturization of the system, so that it could fit on palatal retainer, and allow for permanent unobtrusive usage. The performance of the device was evaluated by measuring the throughput and the accuracy as defined in ISO 9241-9 standard. Two extra measures proposed in the literature, target re-entry and movement offset, were used for the evaluation of the accuracy. The measured throughput values were situated between 78% and 88% of the throughput rates of regular computer joysticks.
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Leonard, James W. Jr. "Replacing indirect manual assistive solutions with hands-free, direct selection." Wright State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=wright1309282777.

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Faneuff, Jeffery. "Spatial, spectral, and perceptual nonlinear noise reduction for hands-free microphones in a car." Link to electronic thesis, 2002. http://www.wpi.edu/Pubs/ETD/Available/etd-0806102-214423.

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Faneuff, Jeffery J. "Spatial, Spectral, and Perceptual Nonlinear Noise Reduction for Hands-free Microphones in a Car." Digital WPI, 2002. https://digitalcommons.wpi.edu/etd-theses/926.

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"Speech enhancement in an automobile is a challenging problem because interference can come from engine noise, fans, music, wind, road noise, reverberation, echo, and passengers engaging in other conversations. Hands-free microphones make the situation worse because the strength of the desired speech signal reduces with increased distance between the microphone and talker. Automobile safety is improved when the driver can use a hands-free interface to phones and other devices instead of taking his eyes off the road. The demand for high quality hands-free communication in the automobile requires the introduction of more powerful algorithms. This thesis shows that a unique combination of five algorithms can achieve superior speech enhancement for a hands-free system when compared to beamforming or spectral subtraction alone. Several different designs were analyzed and tested before converging on the configuration that achieved the best results. Beamforming, voice activity detection, spectral subtraction, perceptual nonlinear weighting, and talker isolation via pitch tracking all work together in a complementary iterative manner to create a speech enhancement system capable of significantly enhancing real world speech signals. The following conclusions are supported by the simulation results using data recorded in a car and are in strong agreement with theory. Adaptive beamforming, like the Generalized Side-lobe Canceller (GSC), can be effectively used if the filters only adapt during silent data frames because too much of the desired speech is cancelled otherwise. Spectral subtraction removes stationary noise while perceptual weighting prevents the introduction of offensive audible noise artifacts. Talker isolation via pitch tracking can perform better when used after beamforming and spectral subtraction because of the higher accuracy obtained after initial noise removal. Iterating the algorithm once increases the accuracy of the Voice Activity Detection (VAD), which improves the overall performance of the algorithm. Placing the microphone(s) on the ceiling above the head and slightly forward of the desired talker appears to be the best location in an automobile based on the experiments performed in this thesis. Objective speech quality measures show that the algorithm removes a majority of the stationary noise in a hands-free environment of an automobile with relatively minimal speech distortion."
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Laverty, Stephen William. "Detection of Nonstationary Noise and Improved Voice Activity Detection in an Automotive Hands-free Environment." Link to electronic thesis, 2005. http://www.wpi.edu/Pubs/ETD/Available/etd-051105-110646/.

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Ma, Hsu-Hao, and 馬珝皓. "OmniKinect: Hands-free Appliances Control System." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/39285143353257579501.

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碩士<br>銘傳大學<br>資訊傳播工程學系碩士班<br>100<br>Microsoft released the Kinect in 2010. It can capture the user’s depth information and use the body to replace the traditional remote control machine, so every player can feel unprecedented entertainment experience. Kinect is reasonable and powerful, so it is attractive to a lot of developers in industry or researchers to develop innovated applications. The Kinect sensor has the limitation in the detection angle and range. If user will want to control many appliances, every appliance must prepare its dedicated device. According to this research, it only needs one Kinect that can control many appliances. Besides, this research uses an Arduino as IR LED controller to send remote control signals to operate machine. So user can use his hands to replace the remote control at home. Therefore, Kinect and Arduino can let our life be simple. When a user enters the sensing area, our system can detect the human skeleton by Microsoft Kinect SDK. Our system can also calculate the 3D transform to recover user&apos;&apos;s pose. If the user raises his hand to point at an appliance, he can specify that device to power on/off and use his gestures to control it. Four gestures are also defined for the most important control signals such as forward, backward, up and down. Our system can also extend to eight gestures for extra commands including escape command. The control system, without traditional remote controller on hand, can make the appliances control easier in digital home.
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Wu, H. Z., and 吳欣儒. "Echo Cancellation and Noise Control in Hands-free Communication systems." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/85107860078083571190.

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碩士<br>國立交通大學<br>電信工程系<br>88<br>Hands-free communication systems usually suffer from echo and environment noise. They exacerbate the communication quality. In this thesis, we present a unified approach of echo cancellation and noise control systems which are categorized into two classes. A new parallel structure is also proposed. We analyze and compare the residual error of both parallel and cascade structures. The theoretical analysis and the computer simulations show that the parallel structure has larger convergent ERLE than the cascade structure. We propose the implementation of impulse response measurements and suggest the subbanding parallel structure of echo and noise cancellation in a car chamber. This accelerates convergence rate and reduces the computation complexities.
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Chang, Chen-Yu, and 張振宇. "Hands-Free Viewing Control in VR Environments by Tracking Facial Visual Information." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/97660851068422355986.

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碩士<br>國立交通大學<br>資訊工程系<br>87<br>In the conventional virtual reality navigation system, the viewing of the scene information is controlled by some peripherals, e.g. a mouse or a trackball. Users have to use their hands to control the device; this is quite inconvenient and unnatural. In this thesis, we will develop a facial tracking system using only one camera. We mount a calibrated TV camera in the front of the human face to properly capture the images of the human facial motions. We assume that the eyes and the mouth on the human face are coplanar in 3-D space, so a mathematical transformation can be derived to estimate the relationship between two different images of the same face. Furthermore, the facial motion parameter can be decomposed from the derived 3x3 transformation matrix. When the facial motion parameter are obtained, they can be transmitted to the VR navigation system to change the viewing specification. Hence, without using hands to control any input device, users can use head movement to browse the virtual world naturally. In our methods, we use a single camera mounted in the front of the human face, and carry out camera intrinsic calibration in advance. Then any rotation (mainly in the left-right or the up-down direction) and any translation (mainly in the front-back direction) of the head movement can be captured by the camera. We first select a reference face image from the captured images; this reference face image is generally taken when the human face is in a neutral pose with the face looking toward the camera. After that, we can use the derived formulation to determine the motion parameters of the head rotation (R3x3) and translation (T3x1) by making use of the reference face image and the currently captured facial image. Finally, the motion parameters are transmitted to the VR platform to do the viewing control.
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Books on the topic "Hands-free control"

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Frerk, Christopher, and Takashi Asai. The airway in anaesthetic practice. Edited by Michel M. R. F. Struys. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199642045.003.0048.

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This chapter provides a comprehensive review of current airway management set against its historical context and likely future developments in the field. Developments in equipment design are discussed against the background of a short review of the anatomy and physiology relevant to clinical airway management. An exploration of airway devices examines progress in design from the first facemasks and early hands-free delivery systems, through to current second-generation supraglottic airways and the future of providing improved protection against aspiration. Continuing advances in tracheal tube and cuff design are set alongside developments in techniques and equipment for laryngoscopy and possibilities for supplementing capnography in confirmation of correct tube placement within the trachea. The use of newer drugs to facilitate control of airway reflexes is also discussed. The importance of using optimal evidence-based techniques in airway management is highlighted in the reduction of complications. This covers preoperative evaluation of the airway, planning a strategy, induction of anaesthesia, and establishing a clear airway through to safe termination of anaesthesia, emergence, tracheal extubation, and recovery. Techniques for dealing with complications if they arise are described. Drawing on lessons from the Fourth National Audit Project of the Royal College of Anaesthetists and the Difficult Airway Society ‘Major complications of airway management in the United Kingdom’ (NAP4) and the general literature, emphasis is placed on high-risk areas of airway management and areas where the existing knowledge base is not covered in depth in other texts.
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Book chapters on the topic "Hands-free control"

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Madden, Brian, James Condron, Ted Burke, and Eugene Coyle. "Augmented control of hands free voice prostheses." In IFMBE Proceedings. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-89208-3_357.

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Mustaquim, Moyen Mohammad. "Use of Hands-Free Mouse for Game Control." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22095-1_38.

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Ghadekar, Premanand, Pragya Korpal, Pooja Chendake, Raksha Bansal, Apurva Pawar, and Siddhi Bhor. "Real-Time Hands-Free Mouse Control for Disabled." In Machine Learning and Information Processing. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4859-2_16.

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Wang, Yuanyuan, Tomoki Hidaka, Yukiko Kawai, and Jiro Okuda. "Why Cannot Control Your Smartphones by Thinking? Hands-Free Information Control System Based on EEG." In Innovation in Medicine and Healthcare 2015. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23024-5_50.

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Wei, Lai, and Huosheng Hu. "Multi-modality — EMG and Visual Based Hands-Free Control of an Intelligent Wheelchair." In Intelligent Robotics and Applications. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16587-0_60.

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Breining, Christina. "On using MLPs for step size control in echo cancellation for hands-free telephone sets." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0020260.

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Khoshnam, Mahta, Eunice Kuatsjah, Xin Zhang, and Carlo Menon. "Hands-Free EEG-Based Control of a Computer Interface Based on Online Detection of Clenching of Jaw." In Bioinformatics and Biomedical Engineering. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56148-6_44.

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Tamura, Hiroki, Takao Manabe, Takafumi Goto, Yuki Yamashita, and Koichi Tanno. "A Study of the Electric Wheelchair Hands-Free Safety Control System Using the Surface-Electromygram of Facial Muscles." In Intelligent Robotics and Applications. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16587-0_10.

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Nitsch, Bernhard H. "Real-Time Implementation of the Exact Block NLMS Algorithm for Acoustic Echo Control in Hands-Free Telephone Systems." In Acoustic Signal Processing for Telecommunication. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4419-8644-3_4.

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Rechy-Ramirez, Ericka Janet, and Huosheng Hu. "Flexible Bi-modal Control Modes for Hands-Free Operation of a Wheelchair by Head Movements and Facial Expressions." In New Trends in Medical and Service Robots. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05431-5_8.

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Conference papers on the topic "Hands-free control"

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Sugiyama, Akihiko, Thanh Phong Hua, Regine le Bouquin Jeannes, and Gerard Faucon. "A Comparative Study of Adaptation-Mode Control for Generalized Sidelobe Cancellers in Human-Robot Communication." In 2008 Hands-Free Speech Communication and Microphone Arrays (HSCMA '08). IEEE, 2008. http://dx.doi.org/10.1109/hscma.2008.4538676.

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Zumbado, J. R., P. H. Curiel, and S. Schreiner. "Hands-Free Control Interfaces for an Extra Vehicular Jetpack." In 2013 IEEE Aerospace Conference. IEEE, 2013. http://dx.doi.org/10.1109/aero.2013.6497138.

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Hirsch, Marco, Jingyuan Cheng, Attila Reiss, Mathias Sundholm, Paul Lukowicz, and Oliver Amft. "Hands-free gesture control with a capacitive textile neckband." In UbiComp '14: The 2014 ACM Conference on Ubiquitous Computing. ACM, 2014. http://dx.doi.org/10.1145/2634317.2634328.

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Ngo Ba Viet, Nguyen Thanh Hai, and Ngo Van Thuyen. "Hands-free control of an electric wheelchair using face behaviors." In 2017 International Conference on System Science and Engineering (ICSSE). IEEE, 2017. http://dx.doi.org/10.1109/icsse.2017.8030831.

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Assad, Chris, Jaakko Karras, Javier Rodriguez, et al. "Live demonstration: BioSleeve, a wearable hands-free gesture control interface." In 2016 IEEE SENSORS. IEEE, 2016. http://dx.doi.org/10.1109/icsens.2016.7808566.

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Takahashi, Kazuhiko, Takashi Nakauke, and Masafumi Hashimoto. "Remarks on hands-free manipulation system using simple brain-computer interface." In 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control. IEEE, 2006. http://dx.doi.org/10.1109/cacsd-cca-isic.2006.4776662.

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Takahashi, Kazuhiko, Takashi Nakauke, and Masafumi Hashimoto. "Remarks on Hands-Free Manipulation System Using Simple Brain-Computer Interface." In 2006 IEEE International Conference on Control Applications. IEEE, 2006. http://dx.doi.org/10.1109/cca.2006.285908.

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Peterson, Dale L., and Mont Hubbard. "Yaw Rate and Velocity Tracking Control of a Hands-Free Bicycle." In ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-68948.

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The control of a bicycle has been well studied when a steer torque is used as the control input. Less has been done to investigate the control of a hands free bicycle through the rider’s lean relative to the bicycle frame. In this work, we extend a verified benchmark bicycle model to include a rider with the ability to lean in and out of the plane of the bicycle frame. A multi-input multi-output LQR state feedback controller is designed with the control objective being the tracking of a reference yaw rate and rear wheel angular velocity through the use of rider lean torque and rear wheel (pedaling) torque. The LQR controller is tested on the nonlinear model and numerical simulation results are presented. Conclusions regarding the required lean angle of the rider relative to the bicycle frame necessary to execute a steady turn are made, as well as observations of the effects of right half plane zeros in the transfer function from rider lean torque to yaw rate.
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Ghorbel, Agnes, Nader Ben Amor, and Mohamed Jallouli. "An embedded real-time hands free control of an electrical wheelchair." In 2014 Visual Communications and Image Processing (VCIP). IEEE, 2014. http://dx.doi.org/10.1109/vcip.2014.7051544.

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Chun Sing Louis Tsui, Pei Jia, John Q. Gan, Huosheng Hu, and Kui Yuan. "EMG-based hands-free wheelchair control with EOG attention shift detection." In 2007 IEEE International Conference on Robotics and biomimetics (ROBIO). IEEE, 2007. http://dx.doi.org/10.1109/robio.2007.4522346.

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Reports on the topic "Hands-free control"

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Valiton, Jeff, Scott Grigsby, and Tim Choate. Integrated, Hands-Free Control Suites for Maintenance Wearable Computers-VHIC. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada387050.

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McMillan, Grant R., Gloria L. Calhoun, Barbara J. Masquelier, Scott S. Grigsby, and Laurie L. Quill. Comparison of Hands-Free Versus Conventional Wearable Computer Control for Maintenance Applications. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada387231.

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