Zhuxin Dong

Determination of mechanical properties of soft tissue scaffolds by atomic force microscopy nanoindentation

While the determination of mechanical properties of a hard scaffold is relatively straightforward, the mechanical testing of a soft tissue scaffold poses significant challenges due in part to its fragility. Here, we report a new approach for characterizing the stiffness and elastic modulus of a soft scaffold through atomic force microscopy (AFM) nanoindentation. Using collagen-chitosan hydrogel scaffolds as model soft tissue scaffolds, we demonstrated the feasibility of using AFM nanoindentation to determine a force curve of a soft tissue scaffold. A mathematical model was developed to ascertain the stiffness and elastic modulus of a scaffold from its force curve obtained under different conditions. The elastic modulus of a collagen-chitosan (80%/20%, v/v) scaffold is found to be 3.69 kPa. The scaffold becomes stiffer if it contains more chitosan. The elastic modulus of a scaffold composed of 70% collagen and 30% chitosan is about 11.6 kPa. Furthermore, the stiffness of the scaffold is found to be altered significantly by extracellular matrix deposited from cells that are grown inside the scaffold. The elastic modulus of collagen-chitosan scaffolds increased from 10.5 kPa on day 3 to 63.4 kPa on day 10 when human foreskin fibroblast cells grew inside the scaffolds. Data acquired from these measurements will offer new insights into understanding cell fate regulation induced by physiochemical cues of tissue scaffolds.

Hand-written character recognition using MEMS motion sensing technology

In this paper, a micro inertial measurement unit (muIMU) based on micro electro mechanical systems (MEMS) sensors is applied to sense the motion information produced by characters written by human subjects. The muIMU is built to record the three-dimensional accelerations and angular velocities of the motions during hand-writing. (Here we write the characters in a plane, so only two accelerations and one angular velocity are taken from muIMU in processing the data discussed in this paper). Then, we compared the effectiveness of data processing methods such as FFT (fast Fourier transform) and DCT (discrete cosine transform) by showing their corresponding experimental results. Subsequently, we gave an analysis of these two methods, and chose DCT as the preferred data processing method. For character recognition (26 English alphabets and 10 numerical digits), unsupervised network self-organizing map (SOM) is applied to classify the characters and comparatively good results are obtained. Our goal is to show the feasibility of character recognition based on selected sensor motion information, and provide a potential technology for human-gesture recognition based on MEMS motion sensors.

An Attitude Compensation Technique for a MEMS Motion Sensor Based Digital Writing Instrument

A MAG-muIMU which is based on MEMS gyroscopes, accelerometers, and magnetometers is developed for real-time estimation of human hand motions. Appropriate filtering, transformation and sensor fusion techniques are combined in the ubiquitous digital writing instrument to record handwriting on any surface. In this paper, we discuss the design of an extended Kalman filter based on MAG-muIMU (micro inertial measurement unit with magnetometers) for real-time attitude tracking. The filter utilizes the gyroscope propagation for transient updates and correction by reference field sensors, such as gravity sensors, magnetometers or star trackers. A process model is derived to separate sensor bias and to minimize wideband noise. The attitude calculation is based on quaternion which, when compared to Euler angles, has no singularity problem. Testing with synthetic data and actual sensor data proved the filter will converge and accurately track the attitude of a rigid body. Our goal is to implement this algorithm for motion recognition of a 3D ubiquitous digital pen.

Real-time written-character recognition using MEMS motion sensors: Calibration and experimental results

A Micro Inertial Measurement Unit (μIMU) based on Micro Electro Mechanical Systems (MEMS) sensor is applied to sense the motion information produced by human subjects. The μIMU is built with three-dimensional accelerometer. During our experiments, although we write the characters in a plane, all the three-dimensional acceleration information is taken from μIMU in processing data as the third dimension is very helpful to be applied in practical application. In our previous work, the effectiveness of different data processing methods including Fast Fourier Transform (FFT) and Discrete Cosine Transform (DCT) are compared, thus the latter, which is better, is adopted in this paper. Also, Hidden Markov Models (HMM) is introduced and used as a tool to realize hand gesture classification. With this method, new experimental results of hand-written recognition are obtained and stated in this paper. Five Arabic numbers, 0–4, are written forty times by two different persons and we utilize all the data as training samples. Then when another new 29 samples are input to the network for recognition, we obtain a high correct rate at 93%. Ultimately, this technology will provide the feasibility of character recognition and potential for humangesture recognition.

Handwriting tracking based on coupled μIMU/electromagnetic resonance motion detection

We have recently developed a ubiquitous digital writing instrument system based on a micro inertial measurement unit (mulMU), which consists of MEMS (micro- electro-mechanical system), accelerometers and gyroscopes, to compute the position of a marker through double integration of the acceleration measured, so as to real-time record and recognize human handwriting motion in a large writing area, i.e., a large whiteboard or screen. Owing to the random errors that exist in the MEMS sensors, the accuracy of the position estimate degrades with time. Although Kalman filtering algorithm provides a good navigation tracking solution, its accuracy depends on the amount of position information given about the target. In vehicles, the global positioning system (GPS) can be used to augment an IMU with absolute position information and improve its tracking accuracy. However, due to indoor-usage and a higher accuracy requirement, the GPS is not suitable for updating a mulMU used for hand-motion tracking with absolute position information. In this paper, we propose a novel position estimation method which makes use of an electromagnetic resonance (EMR) motion detection board for position information to improve the tracking accuracy of a mulMU-based digital writing instrument. The EMR board cannot provide high resolution (only 3 cm per grid in our case) position information for a large writing area because of high construction cost and poor tracking performance. However, the combined scheme of using the mulMU and the EMR board can compensate their respective weaknesses. The EMR board can bound the mulMU position estimate error and the mulMU can provide detailed information of the handwriting trajectory for the rough locus obtained from the EMR board. Details of the estimation algorithm will be discussed and experimental results of its implementation are compared with the conventional Kalman filtering without the extra position feedback information.

A Novel Real-Time Error Compensation Methodology for μIMU-based Digital Writing Instrument

A micro inertial measurement unit (μlMU) which is based on Micro-Electro-Mechanical Systems (MEMS) accelerometers and gyroscope sensors is developed for real-time recognition of human hand motion. By using appropriate filtering, transformation and sensor fusion algorithms, a ubiquitous digital writing instrument is produced for recording handwriting on any surface. In this paper, we propose a method for deriving an error feedback to a Kalman filter based on the assumption that writing occurs only in two dimensions i.e. the writing surface is flat. By imposing this constraint, error feedback to the Kalman filter can be derived. Details of the feedback algorithm will be discussed and experimental results of its implementation are compared with the simple Kalman filter without feedback information.

Carbon Nanofiber Nanoelectrode Array: Effect of Process Conditions on Reliability

Nanoelectrode arrays (NEA) using 1-D nanomaterials as the electrode material have shown promise for biosensing applications. Vertical, freestanding, individual carbon nanofibers (CNFs) on patterned substrates constitute one example of NEA in the literature. The development of a biosensor system using this NEA first requires reliability studies prior to undertaking system integration with microfluidics and sample handling aspects. Here, we have investigated the effect of temperature and process conditions on the diameters and quality of the CNFs using atomic force microscopy (AFM). A Taguchi approach is employed to study the temperature effect in etched and unetched CNFs using AFM followed by a statistical analysis.

Atomic force microscopy based nano manipulation towards CNT-ISFET pH sensing system

In this paper, we present a novel means by which nano manipulation can be realized on a field effect transistor (FET) surface. Using atomic force microscopy (AFM) tip as a manipulation tool, micro and nano scale channels are created between the gap of a pair of gold (Au) electrodes. Following a dielectrophoresis (DEP) process, carbon nanotubes (CNTs) are deposited and aligned perfectly inside the channels cut by the AFM. Then, the two electrodes are bridged and ready to be developed as an ion-selective field effect transistor (ISFET) structure that has the potential to work as a high-performance pH sensor. Owing to the unique electrical properties of CNTs, such as conductivity (either metallic or semiconducting) and great current carrying capacity (∼1 TA/cm3), there is a huge possibility that this CNT-based ISFET system is a much better replacement for the existing ISFET-based pH sensors. The pH sensing system will be much more compact, cheaper and reproducible, and no longer need outside amplifier circuits, which will have huge benefits in industry, biology as well as medicine.

Force measurement study of engineered collagen-chitosan scaffold using Atomic Force Microscopy

The structure and properties of scaffold are important in cell-based tissue engineering, especially the mechanical property. Here, we quantify the dynamic oscillatory mechanical behavior of two kinds of porous collagen/chitosan scaffolds. The Youngs Modulus were measured in PBS using Atomic Force Microscopy (AFM)-based nano-indentation in response to an imposed oscillatory deformation as a function of force, which can be converted to Youngs Modulus. Collagen/chitosan scaffolds with different ratio (8:2 and 7:3, V/V), which already showed good properties for cell culture, were tested. The Youngs Modulus of collagen/chitosan scaffold with ratio 7:3 is bigger than that of 8:2, which is consistent with our expectation. Force curves were obtained first from indentation, and then Youngs Modulus was determined using a proper Hertz contact mathematical model. Meanwhile, the mechanical properties of mice pancreas and heart were obtained as controls. The results indicated that AFM-based nano-indentation is a good method for the mechanical property testing of porous scaffold.

Design, fabrication and testing of CNT based ISFET for Nano pH sensor application: A preliminary study

In recent years, there has been increasing interest in monitoring and controlling of pH. It has become an important aspect of many industrial wastewater treatment processes. At the same time, the demand for smaller electronic devices used for various industrial and commercial applications has greatly increased. Micro and nano materials, such as Carbon Nanotubes (CNTs), are known for their excellent electrical and mechanical properties, as well as for their small size, therefore they are good candidates to manufacture micro or nano electronic devices. These devices can be used for pH control. However, this cannot be achieved unless CNTs with metallic or semiconducting band structures can be successfully deposited and separated. In these processes, microchip fabrication and deposition of CNTs using Dielectrophoresis (DEP) are involved. Comparing with some traditional pH sensors, which mainly consist of Ion-Sensitive Field Effect Transistor (ISFET), signal operational amplifier and Analog Digital Convert (ADC), Nano pH sensor with CNTs may provide more benefits owing to their unique properties. For example, 70–80% of multi-walled CNTs (MWCNTs) are metallic and have high current density, which means this kind of micro device has a linear relationship of I–V characteristic and can produce signal strong enough to make operational amplifying circuits unnecessary. In addition, to manufacture smaller devices more functional becomes possible as CNTs are tiny and compact.