To fulfill the needs for accurate trajectory tracking with large displacement in a handheld instrument, a 3-DOF serial compliant mechanism is developed. The mechanism is compact with a total length less than 150 mm and a maximum diameter of 22 mm. Two flexures are developed using different rapid prototyping techniques: one 3-DOF flexural lever made of Vero-Gray by Polyjet and a 1-DOF translational flexure made of stainless steel by Direct Metal Laser Sintering (DMLS). Analytical and Finite Element (FE) models are developed for the proposed flexural mechanisms. Experiments are conducted on a prototype. To improve the tracking accuracy, the hysteretic nonlinearities of the system are modeled using Prandtl-Ishlinskii model. Inverse feedforward controller is implemented to linearize the relationship between input and output. The tracking errors are reduced while maintaining a fast response of the system. The total tracking errors are identified individually for each axis and then compensated. Tracking performances of the tool tip are evaluated experimentally with different inputs. The RMS tracking error of the proposed mechanism is lower than 1 µm in all axes, which is improved more than four times compared to the previous systems.

Making changes of cells function by regulating the external mechanical environment is one of the major interests in the mechanobiology field. Based on extensive studies, force at nano-to-micro newton and geometric shape changes at nano to-micrometer are the physical stimuli that can be sensed by cells. It has been postulated that controllable cell responses can be produced by activating diversity of mechanosesory proteins through physical changes of force or shape. In this paper, a real-time machine vision algorithm is proposed to improve the efficiency and robustness of the cell membranes strain calculation. The proposed adaptive image thresholding method with modified numerical implementation is able to apply on all the images captured in the deforming process to extract the deformed cell boundary in real-time. Based on the proposed method, the cell membrane strain is modeled and controlled to deform the cell into a predefined deformation. It enables biologists to study the biochemical changes within the cell by providing a controllable geometric changes. It also expects that a particular cell status or function could be produced by giving a proper deformation.

In this paper, we propose a novel anti-phase tremor compensation method using surface electromyography (SEMG) and accelerometer (ACC). The usefulness of the SEMG signal is that it precedes the generated joint movement by 20 100 ms (electromechanical delay, EMD). Hence by detecting the tremor in advance, there is enough time window to do the necessary computation and to actuate the antagonist muscle by Functional Electrical Stimulation (FES). This is also possible because the time taken for FES to actuate the muscle is significantly less than that of the neural signal, as detected by SEMG. Specifically, what is proposed in this paper is algorithm to an estimate the EMD and to determine when to start/stop the FES such that anti-phase tremor cancellation. Experimental result from one Essential Tremor patient show 57% reduction in tremor power as measured by the ACC.

Inertial measurement units (IMU) consist of accelerometers. Estimation accuracy of acceleration in a particular direction depends on how accurately accelerometers are placed at desired or ideal orientations. The estimation inaccuracy which results from inaccurate orientation of an accelerometer can be eliminated if the orientation error or the angle between the actual and the ideal orientations is known. This paper presents a method of identification of the accelerometer orientation errors without requiring any rotational motion of the IMU in which accelerometers are placed. It also presents a method of compensation for the inaccuracy of acceleration estimation due to the accelerometer orientation errors using angular motion information.

This paper presents a 3-DOF low-cost hand-held micromanipulator driven by 3 piezoelectric actuators and built using rapid prototyping. Traditional pin and ball joints have been commonly replaced by flexure-based methods in the field of micromanipulation. Utilization of flexure-based joints have several advantages like the non-existence of backlash and assembly errors. However, most of the present flexure-based mechanisms are bulky and not suitable for hand-held applications. It is difficult and expensive to make such compact mechanism using traditional machining methods. In additional, traditional machining methods are limited to simple design. To reduce the cost of fabrication and also to allow more complex designs, Objet (a rapid prototyping machine) is proposed to be used to build the mechanism. With regards to hand-held applications, the size of the mechanism is a constraint. Hence, a parallel manipulator design is the preferred choice as compared to a serial mechanism because of its rigidity, compactness, and simplicity in design. For the illustration of an application, the mechanism is designed with an intraocular needle attached to it. Possible applications of this design include enhancement of performance in microsurgery and cell micromanipulation. Experiments are also conducted to evaluate the manipulator's tracking performance of the needle tip at a frequency of 10 Hz.

With the increasing popularity of actuators involving smart materials like piezoelectric, control of such materials becomes important. The existence of the inherent hysteretic behavior hinders the tracking accuracy of the actuators. To make matters worse, the hysteretic behavior changes with rate. One of the suggested ways is to have a feedforward controller to linearize the relationship between the input and output. Thus, the hysteretic behavior of the actuator must be first modeled by sensing the relationship between the input voltage and output displacement. Unfortunately, the hysteretic behavior is dependent on individual actuator and also environmental conditions like temperature. In this fast moving world, time is money and it is very costly to model the hysteresis regularly. In addition, the hysteretic behavior of the actuators also changes with age. Base on the studies done on the phenomena hysteretic behavior with rate, this paper proposes an adaptive rate-dependent feedforward controller with Prandtl-Ishlinskii (PI) hysteresis operators for piezoelectric actuators. This adaptive controller is achieved by adapting the coefficients to manipulate the weights of the play operators. Actual experiments are conducted to demonstrate the effectiveness of the adaptive controller.

Currently there is a lack of objective clinical diagnosis and classification of tremor is difficult when it is subtle. Thus in previous work, a sensing system has been developed to quantify pathological tremor in human upper limb. In this paper, a Kalman filter algorithm to fuse information from accelerometers and surface electromyography is proposed. As the ground truth, an optical motion tracking system will be utilized. Then two sensor fusion algorithms based on Kalman filter are formulated to estimate the joint angle of the limb from the reading of accelerometers and surface EMG. Initial results using tremor data from two Parkinson's disease patients show promising future in this sensor fusion. The sensing system and the algorithms proposed are useful for actively compensating the tremor and helping the clinicians in tremor diagnostics.

An optical sensing system has been developed using a pair of orthogonally placed position sensitive detectors (PSD) to track 3D displacement of a microsurgical instrument tip in real-time. An infrared (IR) diode is used to illuminate the workspace. A ball is attached to the tip of an intraocular shaft to reflect IR rays onto the PSDs. Instrument tip position is then calculated from the centroid positions of reflected IR light on the respective PSDs. The system can be used to assess the accuracy of hand-held microsurgical instruments and operator performance in micromanipulation tasks, such as microsurgeries. In order to eliminate inherent nonlinearity of the PSDs and lenses, calibration is performed using a feedforward neural network. After calibration, percentage RMS error is reduced from about 5.46 % to about 0.16%. The system RMS noise is about 0.7 mum. The sampling rate of the system is 250 Hz.