Dynamic Gesture Recognition Using a Smart Glove in Hand-Assisted Laparoscopic Surgery

This paper presents a methodology for movement recognition in hand-assisted laparoscopic surgery using a textile-based sensing glove. The aim is to recognize the commands given by the surgeon’s hand inside the patient’s abdominal cavity in order to guide a collaborative robot. The glove, which incorporates piezoresistive sensors, continuously captures the degree of flexion of the surgeon’s fingers. These data are analyzed throughout the surgical operation using an algorithm that detects and recognizes some defined movements as commands for the collaborative robot. However, hand movement recognition is not an easy task, because of the high variability in the motion patterns of different people and situations. The data detected by the sensing glove are analyzed using the following methodology. First, the patterns of the different selected movements are defined. Then, the parameters of the movements for each person are extracted. The parameters concerning bending speed and execution time of the movements are modeled in a prephase, in which all of the necessary information is extracted for subsequent detection during the execution of the motion. The results obtained with 10 different volunteers show a high degree of precision and recall

The Archaeological Record Speaks: Bridging Anthropology and Linguistics

This paper examines the origins of language, as treated within Evolutionary Anthropology, under the light offered by a biolinguistic approach. This perspective is presented first. Next we discuss how genetic, anatomical, and archaeological data, which are traditionally taken as evidence for the presence of language, are circumstantial as such from this perspective. We conclude by discussing ways in which to address these central issues, in an attempt to develop a collaborative approach to them