Abstract
Enabling touch-sensing capability would help appliances understand interaction behaviors with their surroundings. Many recent studies are focusing on the development of electronic skin because of its necessity in various application domains, namely autonomous artificial intelligence (e.g., robots), biomedical instrumentation, and replacement prosthetic devices. An essential task of the electronic skin system is to locally process the tactile data and send structured information either to mimic human skin or to respond to the application demands. The electronic skin must be fabricated together with an embedded electronic system which has the role of acquiring the tactile data, processing, and extracting structured information. On the other hand, processing tactile data requires efficient methods to extract meaningful information from raw sensor data. Machine learning represents an effective method for data analysis in many domains: it has recently demonstrated its effectiveness in processing tactile sensor data. In this framework, this paper presents the implementation of digital signal processing based on FPGAs for tactile data processing. It provides the implementation of a tensorial kernel function for a machine learning approach. Implementation results are assessed by highlighting the FPGA resource utilization and power consumption. Results demonstrate the feasibility of the proposed implementation when real-time classification of input touch modalities are targeted.
Highlights
The skin is one of the main organs of the human body; it helps us to interact with our surroundings through implementing many different and relevant functions, e.g., protection of the inner body organs, detection of cutaneous stimuli, etc
The implementation of real-time embedded electronic system based on the tensorial framework described in Section 3.3 is targeted for the digital signal processing (DSP) of the electronic skin system
Embedding digital signal processing systems into e-skin for tactile data processing has to Embedding digitalconstraints signal processing systems e-skin for e.g., tactilereal-time data processing haslow to comply comply with severe imposed by theinto application, response, power comply with severe constraints imposed by the application, e.g., real-time response, low power with severe constraints imposed application, e.g., real-time response, low power consumption consumption and small size
Summary
The skin is one of the main organs of the human body; it helps us to interact with our surroundings through implementing many different and relevant functions, e.g., protection of the inner body organs, detection of cutaneous stimuli, etc. The development electronic skin (e-skin) is a very and challenging whichan involves many different of and complementary research areas.complex. E-skin tasks designing mechanical of the skin itself The (i.e.,different sensing materials), aretogether still in their infancy and far from being properly addressed even if many research with the embedded digital system for tactile data processing. Still in their infancy and far from being properly even if many research groups are Significant progress in the development of e-skin has been achieved in addressing the topic with different approaches at each level of the problem [3,4,5,6,7,8,9].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
