An optoelectromechanical tactile sensor for detection of breast lumps

Flexible Tactile Sensor Array for Slippage and Grooved Surface Recognition in Sliding Movement

Flexible tactile sensor with contact force sensing and surface texture recognition abilities is crucial for robotic dexterous grasping and manipulation in daily usage. Different from force sensing, surface texture discrimination is more challenging in the development of tactile sensors because of limited discriminative information. This paper presents a novel method using the finite element modeling (FEM) and phase delay algorithm to investigate the flexible tactile sensor array for slippage and grooved surfaces discrimination when sliding over an object. For FEM modeling, a 3 × 3 tactile sensor array with a multi-layer structure is utilized. For sensor array sliding over a plate surface, the initial slippage occurrence can be identified by sudden changes in normal forces based on wavelet transform analysis. For the sensor array sliding over pre-defined grooved surfaces, an algorithm based on phase delay between different sensing units is established and then utilized to discriminate between periodic roughness and the inclined angle of the grooved surfaces. Results show that the proposed tactile sensor array and surface texture recognition method is anticipated to be useful in applications involving human-robotic interactions.

Shape Localization and Recognition Using a Magnetorheological-Fluid Haptic Display

Smart materials such as magnetorheological fluids (MRF) offer an interesting technology for use in haptic displays as changes in the magnetic field are rapid, reversible, and controllable. These interfaces have been evaluated in a number of medical and surgical simulators where they can provide cues regarding the viscoelastic properties of tissues. The objective of the present set of experiments was first to determine whether a shape embedded in the MRF could be precisely localized and second whether 10 shapes rendered in a MRF haptic display could be accurately identified. It was also of interest to determine how the information transfer associated with this type of haptic display compares to that achieved using other haptic channels of communication. The overall performance of participants at identifying the shapes rendered in the MRF was good with a mean score of 73 percent correct and an Information Transfer (IT) of 2.2 bits. Participants could also localize a rigid object in the display accurately. These findings indicate that this technology has potential for use in training manual palpation skills and in exploring haptic shape perception in dynamic environments.

Video-tactile pneumatic sensor for soft tissue elastic modulus estimation

Background

A new sensor for estimating elasticity of soft tissues such as a liver was developed for minimally invasive surgery application.

Methods

By measuring deformation and adjusting internal pressure of the pneumatic sensor head, the sensor can be used to do palpation (indentation) of tissues with wide range of stiffness. A video camera installed within the sensor shell is used to register the radius of the contact area. Based on finite element model simulations and the measured data, elastic modulus of the indented soft tissue can be calculated.

Results and conclusions

Three phantom materials, namely plastic, silicone and gelatin, with varied stiffness were tested. The experimental results demonstrated that the new sensor can obtain highly reliable data with error less than 5%. The new sensor might be served as an instrument in laparoscopic surgery for diagnosis of pathological tissues or internal organs.

Displaying shape haptically using MRF-based device

Smart materials such as magnetorheological fluids (MRF) offer an interesting medium to present viscoelastic cues in haptic displays as changes in the magnetic field are rapid, reversible and controllable. These interfaces have been evaluated in a number of medical and surgical simulators where they can provide cues regarding the viscoelastic properties of tissues. The present experiment determined whether eight different shapes could be identified reliably with a MRF haptic display and compared the information transfer (IT) associated with this type of display with that achieved by other forms of haptic communication. The overall performance of participants at identifying the shapes was good with a mean score of 70% correct and an IT of 2.13 bits. This type of display shows promise as a training tool for simulating tissue properties.

Tactile imaging of an imbedded palpable structure for breast cancer screening

Apart from texture, the human finger can sense palpation. The detection of an imbedded structure is a fine balance between the relative stiffness of the matrix, the object, and the device. If the device is too soft, its high responsiveness will limit the depth to which the imbedded structure can be detected. The sensation of palpation is an effective procedure for a physician to examine irregularities. In a clinical breast examination (CBE), by pressing over 1 cm(2) area, at a contact pressure in the 70-90 kPa range, the physician feels cancerous lumps that are 8- to 18-fold stiffer than surrounding tissue. Early detection of a lump in the 5-10 mm range leads to an excellent prognosis. We describe a thin-film tactile device that emulates human touch to quantify CBE by imaging the size and shape of 5-10 mm objects at 20 mm depth in a breast model using ∼80 kPa pressure. The linear response of the device allows quantification where the greyscale corresponds to the relative local stiffness. The (background) signal from <2.5-fold stiffer objects at a size below 2 mm is minimal.