Smart Gloves for Feeling Results

The broad idea has been around for while, we tried it for tracking a manufacturing process to determine the 'feel' of output based on handling it.   A kind of test that could indicated if maintenance or mixing parameters needed to be updated.   Could see some agricultural applications.  Also, if you can gather data from the gloves, you might be able to look for patterns that predicted other issues.  For example dryness of plants.  Combine it with visual data, and find other patterns of interest?   But at the time the approaches were not discerning enough,   This seems closer.

Smart Glove Works Out What You’re Holding from Its Weight, Shape 
New Scientist
By Chelsea Whyte in ACM
May 29, 2019

Researchers at the Massachusetts Institute of Technology (MIT) have created a smart glove that allows a neural network to learn the shape and weight of an object, a development that could be applied to robots in factories or homes, and could even provide insights about how the human grip works. The researchers attached a force-sensitive film to the palms and fingers of a knitted glove and stitched a network of 64 conductive silver threads into it. When pressure is applied to the 548 points where the threads intersect, the electrical resistance of the film beneath decreases, allowing the glove to detect the weight and shape of an object the wearer is holding, as well as the pressure created as the hand moves. Said MIT researcher Subramanian Sundaram, "It can tell whether you’re holding an object with a long edge, like a chalkboard eraser, as opposed to something more spherical like a tennis ball.".... ' 

More technical details:
Sensor-Packed Glove Learns Signatures of the Human Grasp
By MIT News 

STAG scalable tactile glove
The "scalable tactile glove" (STAG) is equipped with 548 sensors that capture pressure signals as humans interact with objects.

Wearing a sensor-packed glove while handling a variety of objects, MIT researchers have compiled a massive dataset that enables an AI system to recognize objects through touch alone. The information could be leveraged to help robots identify and manipulate objects, and may aid in prosthetics design.

The researchers developed a low-cost knitted glove, called "scalable tactile glove" (STAG), equipped with about 550 tiny sensors across nearly the entire hand. Each sensor captures pressure signals as humans interact with objects in various ways. A neural network processes the signals to "learn" a dataset of pressure-signal patterns related to specific objects. Then, the system uses that dataset to classify the objects and predict their weights by feel alone, with no visual input needed. .... "