Abstract: Conventional proprioceptive studies use commercial vibrators. Such vibrators have major drawbacks as their amplitude and frequency adjustments are limited or outside the range of frequency that stimulates the specific human biological sensors making them non-specific to each individual or muscle. At times, they are also expensive and not wearable. The presently disclosed subject matter relates to system and method for custom-developed vibrational systems having various adjustable and flexible parameters such as amplitude, frequency, delay time, and other user requirement functions that can work simultaneously and can be applied to different individuals and to different muscle spots. The presently disclosed system and method are robust, compact, wearable, economical, and easy to operate.

Abstract: Disclosed is an acoustic-based biosensing platform that can be utilized in point of care applications and can provide rapid results with both high sensitivity and high selectivity. The sensing platform includes a plurality of piezoelectric cantilevers conjugated with a specific binding member for a bioanalyte of interest. Upon excitation of an excitation cantilever, acoustic feature extraction from response signals can provide information with regard to the presence or quantity of a bioanalyte of interest.

Abstract: The disclosure deals with a system and method for Compressive Sensing, which has been shown to greatly reduce data acquisition and processing burdens by providing mathematical guarantees for accurate signal recovery from far fewer samples than conventionally needed. A generalized Compressive Sensing methodology developed for automated reduction of non-destructive evaluation/structural health monitoring (NDE/SHM) data is effective for multiple types of NDE/SHM systems. The methodology uses Compressive Sensing at two stages in the data acquisition and analysis process to detect damage. The two stages are: (1) temporally undersampled sensor signals from (2) spatially undersampled sensor arrays, resulting in faster data acquisition and reduced data sets without any loss in damage detection ability. In addition, a graphical user interface helps guide and visualize the associated data reconstruction process.

Abstract: An autonomous all-terrain robot for agricultural industries is designed to install support stakes inground on plant beds while being able to self-navigate. Apparatus and method provide a robot having the ability to perform the actions of navigating between plant beds and to determine a precise location and depth to place each supporting stake. The purpose of the stakes is to support the plants with weak stems. Part of some planting processes require stakes to support a plant as it begins to grow. from a two- or three-week-old plant to a fully mature plant. The presently disclosed subject matter provides a machine that can aid in the planting process of both bell peppers and eggplants and similar crops, used to drive stakes into planting beds. The presently disclosed technology (such as specific robotic device or robot) can work 24/7, weather permitting, while providing an efficient and completely hands-free way to install stakes needed in the planting process.

Abstract: Detecting damage in a structure without comparing sensor signals to a baseline signal. Once a structure is interrogated, a process based on a Gaussian Mixture Model is applied to the resulting data set, resulting in quantities for which Mahalanobis distances and Euclidian distances can be determined. A damage index is then determined based on the calculated Euclidian distance. A high value of this damage index coupled with an abrupt change in Mahalanobis distance has been found to be a reliable indicator of damage. Other embodiments may employ a baseline, but determine damage according to ratios of energy values between current and baseline signals.