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Control Systems and Robotics in Bioengineering

A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: closed (30 November 2011) | Viewed by 46735

Special Issue Editor

Department of Mechanical and Biomedical Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China
Interests: robotics manipulation; multirobot system; motion control; cell engineering

Special Issue Information

Dear Colleagues,

This special issue aims to publish pioneered works in control systems and robotics on the forefront of the emerging biology-based engineering discipline. There is increasing number of researchers, who fuse robotics and control engineering principles with the knowledge and tools of molecular life sciences in order to solve contemporary problems through the measurement, modeling, and rational manipulation of biological systems. These researchers are more rapidly creating biology-based technologies to benefit a range of diverse areas including human and environmental health, agriculture, manufacturing, and defense.

Recently, many researchers in controls and robotics have explored complicated problems arising from societal needs and concerns, and directed leading-edge research teams to address those challenge problems, in which design and control of biofunctionalized systems based on measured biological responses are the central issue. Through this special issue, we wish to deliver essential and advanced bioengineering information in applications of control and robotics technologies in life science. In the next few years there will surely be much more exciting developments in this area.

Judging by what we have witnessed so far, this exciting field of control systems and robotics in bioengineering is likely to produce revolutionary breakthroughs over the next decade. The special issue of the journal Sensors will cover different aspects of this field.

Prof. Dr. Dong Sun
Guest Editor

Keywords

  • biorobotics
  • micro/nano robot for bioengineering
  • medical robot
  • manipulation
  • genetic regulatory networks
  • syntheitic biology
  • systems biology
  • biosensor
  • modeling
  • biomolecular, cell and tissue engineering

Published Papers (5 papers)

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787 KiB  
Article
A Robust Kalman Algorithm to Facilitate Human-Computer Interaction for People with Cerebral Palsy, Using a New Interface Based on Inertial Sensors
by Rafael Raya, Eduardo Rocon, Juan A. Gallego, Ramón Ceres and Jose L. Pons
Sensors 2012, 12(3), 3049-3067; https://doi.org/10.3390/s120303049 - 06 Mar 2012
Cited by 24 | Viewed by 9093
Abstract
This work aims to create an advanced human-computer interface called ENLAZA for people with cerebral palsy (CP). Although there are computer-access solutions for disabled people in general, there are few evidences from motor disabled community (e.g., CP) using these alternative interfaces. The proposed [...] Read more.
This work aims to create an advanced human-computer interface called ENLAZA for people with cerebral palsy (CP). Although there are computer-access solutions for disabled people in general, there are few evidences from motor disabled community (e.g., CP) using these alternative interfaces. The proposed interface is based on inertial sensors in order to characterize involuntary motion in terms of time, frequency and range of motion. This characterization is used to design a filtering technique that reduces the effect of involuntary motion on person-computer interaction. This paper presents a robust Kalman filter (RKF) design to facilitate fine motor control based on the previous characterization. The filter increases mouse pointer directivity and the target acquisition time is reduced by a factor of ten. The interface is validated with CP users who were unable to control the computer using other interfaces. The interface ENLAZA and the RKF enabled them to use the computer. Full article
(This article belongs to the Special Issue Control Systems and Robotics in Bioengineering)
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600 KiB  
Article
Fiber Surface Modification Technology for Fiber-Optic Localized Surface Plasmon Resonance Biosensors
by Qiang Zhang, Chenyang Xue, Yanling Yuan, Junyang Lee, Dong Sun and Jijun Xiong
Sensors 2012, 12(3), 2729-2741; https://doi.org/10.3390/s120302729 - 29 Feb 2012
Cited by 38 | Viewed by 10970
Abstract
Considerable studies have been performed on the development of optical fiber sensors modified by gold nanoparticles based on the localized surface plasmon resonance (LSPR) technique. The current paper presents a new approach in fiber surface modification technology for biosensors. Star-shaped gold nanoparticles obtained [...] Read more.
Considerable studies have been performed on the development of optical fiber sensors modified by gold nanoparticles based on the localized surface plasmon resonance (LSPR) technique. The current paper presents a new approach in fiber surface modification technology for biosensors. Star-shaped gold nanoparticles obtained through the seed-mediated solution growth method were found to self-assemble on the surface of tapered optical fibers via amino- and mercapto-silane coupling agents. Transmitted power spectra of 3-aminopropyltrimethoxy silane (APTMS)-modified fiber were obtained, which can verify that the silane coupling agent surface modification method is successful. Transmission spectra are characterized in different concentrations of ethanol and gentian violet solutions to validate the sensitivity of the modified fiber. Assembly using star-shaped gold nanoparticles and amino/mercapto silane coupling agent are analyzed and compared. The transmission spectra of the gold nanoparticles show that the nanoparticles are sensitive to the dielectric properties of the surrounding medium. After the fibers are treated in t-dodecylmercaptan to obtain their transmission spectra, APTMS-modified fiber becomes less sensitive to different media, except that modified by 3-mercaptopropyltrimethoxy silane (MPTMS). Experimental results of the transmission spectra show that the surface modified by the gold nanoparticles using MPTMS is firmer compared to that obtained using APTMS. Full article
(This article belongs to the Special Issue Control Systems and Robotics in Bioengineering)
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479 KiB  
Article
Hand Motion Classification Using a Multi-Channel Surface Electromyography Sensor
by Xueyan Tang, Yunhui Liu, Congyi Lv and Dong Sun
Sensors 2012, 12(2), 1130-1147; https://doi.org/10.3390/s120201130 - 30 Jan 2012
Cited by 72 | Viewed by 10233
Abstract
The human hand has multiple degrees of freedom (DOF) for achieving high-dexterity motions. Identifying and replicating human hand motions are necessary to perform precise and delicate operations in many applications, such as haptic applications. Surface electromyography (sEMG) sensors are a low-cost method for [...] Read more.
The human hand has multiple degrees of freedom (DOF) for achieving high-dexterity motions. Identifying and replicating human hand motions are necessary to perform precise and delicate operations in many applications, such as haptic applications. Surface electromyography (sEMG) sensors are a low-cost method for identifying hand motions, in addition to the conventional methods that use data gloves and vision detection. The identification of multiple hand motions is challenging because the error rate typically increases significantly with the addition of more hand motions. Thus, the current study proposes two new methods for feature extraction to solve the problem above. The first method is the extraction of the energy ratio features in the time-domain, which are robust and invariant to motion forces and speeds for the same gesture. The second method is the extraction of the concordance correlation features that describe the relationship between every two channels of the multi-channel sEMG sensor system. The concordance correlation features of a multi-channel sEMG sensor system were shown to provide a vast amount of useful information for identification. Furthermore, a new cascaded-structure classifier is also proposed, in which 11 types of hand gestures can be identified accurately using the newly defined features. Experimental results show that the success rate for the identification of the 11 gestures is significantly high. Full article
(This article belongs to the Special Issue Control Systems and Robotics in Bioengineering)
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3948 KiB  
Article
A Feedfordward Adaptive Controller to Reduce the Imaging Time of Large-Sized Biological Samples with a SPM-Based Multiprobe Station
by Jorge Otero, Hector Guerrero, Laura Gonzalez and Manel Puig-Vidal
Sensors 2012, 12(1), 686-703; https://doi.org/10.3390/s120100686 - 10 Jan 2012
Cited by 4 | Viewed by 6954
Abstract
The time required to image large samples is an important limiting factor in SPM-based systems. In multiprobe setups, especially when working with biological samples, this drawback can make impossible to conduct certain experiments. In this work, we present a feedfordward controller based on [...] Read more.
The time required to image large samples is an important limiting factor in SPM-based systems. In multiprobe setups, especially when working with biological samples, this drawback can make impossible to conduct certain experiments. In this work, we present a feedfordward controller based on bang-bang and adaptive controls. The controls are based in the difference between the maximum speeds that can be used for imaging depending on the flatness of the sample zone. Topographic images of Escherichia coli bacteria samples were acquired using the implemented controllers. Results show that to go faster in the flat zones, rather than using a constant scanning speed for the whole image, speeds up the imaging process of large samples by up to a 4x factor. Full article
(This article belongs to the Special Issue Control Systems and Robotics in Bioengineering)
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1583 KiB  
Article
Development of a Multisensor-Based Bio-Botanic Robot and Its Implementation Using a Self-Designed Embedded Board
by Chung-Liang Chang, Ming-Fong Sie and Jin-Long Shie
Sensors 2011, 11(12), 11629-11648; https://doi.org/10.3390/s111211629 - 13 Dec 2011
Cited by 2 | Viewed by 8739
Abstract
This paper presents the design concept of a bio-botanic robot which demonstrates its behavior based on plant growth. Besides, it can reflect the different phases of plant growth depending on the proportional amounts of light, temperature and water. The mechanism design is made [...] Read more.
This paper presents the design concept of a bio-botanic robot which demonstrates its behavior based on plant growth. Besides, it can reflect the different phases of plant growth depending on the proportional amounts of light, temperature and water. The mechanism design is made up of a processed aluminum base, spring, polydimethylsiloxane (PDMS) and actuator to constitute the plant base and plant body. The control system consists of two micro-controllers and a self-designed embedded development board where the main controller transmits the values of the environmental sensing module within the embedded board to a sub-controller. The sub-controller determines the growth stage, growth height, and time and transmits its decision value to the main controller. Finally, based on the data transmitted by the sub-controller, the main controller controls the growth phase of the bio-botanic robot using a servo motor and leaf actuator. The research result not only helps children realize the variation of plant growth but also is entertainment-educational through its demonstration of the growth process of the bio-botanic robot in a short time. Full article
(This article belongs to the Special Issue Control Systems and Robotics in Bioengineering)
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