Measuring Gait Using a Ground Laser Range Sensor

This paper describes a measurement system designed to register the displacement of the legs using a two-dimensional laser range sensor with a scanning plane parallel to the ground and extract gait parameters. In the proposed methodology, the position of the legs is estimated by fitting two circles with the laser points that define their contour and the gait parameters are extracted applying a step-line model to the estimated displacement of the legs to reduce uncertainty in the determination of the stand and swing phase of the gait. Results obtained in a range up to 8 m shows that the systematic error in the location of one static leg is lower than 10 mm with and standard deviation lower than 8 mm; this deviation increases to 11 mm in the case of a moving leg. The proposed measurement system has been applied to estimate the gait parameters of six volunteers in a preliminary walking experiment

A flexible sensor technology for the distributed measurement of interaction pressure

We present a sensor technology for the measure of the physical human-robot interaction pressure developed in the last years at Scuola Superiore Sant'Anna. The system is composed of flexible matrices of opto-electronic sensors covered by a soft silicone cover. This sensory system is completely modular and scalable, allowing one to cover areas of any sizes and shapes, and to measure different pressure ranges. In this work we present the main application areas for this technology. A first generation of the system was used to monitor human-robot interaction in upper- (NEUROExos; Scuola Superiore Sant'Anna) and lower-limb (LOPES; University of Twente) exoskeletons for rehabilitation. A second generation, with increased resolution and wireless connection, was used to develop a pressure-sensitive foot insole and an improved human-robot interaction measurement systems. The experimental characterization of the latter system along with its validation on three healthy subjects is presented here for the first time. A perspective on future uses and development of the technology is finally drafted

Measuring Oscillating Walking Paths with a LIDAR

This work describes the analysis of different walking paths registered using a Light Detection And Ranging (LIDAR) laser range sensor in order to measure oscillating trajectories during unsupervised walking. The estimate of the gait and trajectory parameters were obtained with a terrestrial LIDAR placed 100 mm above the ground with the scanning plane parallel to the floor to measure the trajectory of the legs without attaching any markers or modifying the floor. Three different large walking experiments were performed to test the proposed measurement system with straight and oscillating trajectories. The main advantages of the proposed system are the possibility to measure several steps and obtain average gait parameters and the minimum infrastructure required. This measurement system enables the development of new ambulatory applications based on the analysis of the gait and the trajectory during a walk

Dynamic Mutual Capacitive Sensor for Human Interactions.

This dissertation introduces the novel concept of removing the ground conductive plate by utilizing body capacitance as the ground in the capacitive sensor, whereby circuit pressure sensing can occur with only one plate and one dielectric. Additionally, body capacitance sensing was limited to a binary touch-no-touch output, whereas the method presented here can sense various applied pressures. The resulting circuit acts as an antenna that receives local capacitance signals from a human interaction. The advantage of this design is that it allows for both proximity sensing and pressure sensing (once the body part is touching the dielectric material). This setup is ideal for a z-axis dimensional interface for touchscreen devices, as well as pressure sensing palpation or planter region interaction

高齢者とともに歩行する社会的支援ヒューマノイドに関する研究

筑波大学 (University of Tsukuba)201

Neuromechanical and environment aware machine learning tool for human locomotion intent recognition

Current research suggests the emergent need to recognize and predict locomotion modes (LMs) and LM transitions to allow a natural and smooth response of lower limb active assistive devices such as prostheses and orthosis for daily life locomotion assistance. This Master dissertation proposes an automatic and user-independent recognition and prediction tool based on machine learning methods. Further, it seeks to determine the gait measures that yielded the best performance in recognizing and predicting several human daily performed LMs and respective LM transitions. The machine learning framework was established using a Gaussian support vector machine (SVM) and discriminative features estimated from three wearable sensors, namely, inertial, force and laser sensors. In addition, a neuro-biomechanical model was used to compute joint angles and muscle activations that were fused with the sensor-based features. Results showed that combining biomechanical features from the Xsens with environment-aware features from the laser sensor resulted in the best recognition and prediction of LM (MCC = 0.99 and MCC = 0.95) and LM transitions (MCC = 0.96 and MCC = 0.98). Moreover, the predicted LM transitions were determined with high prediction time since their detection happened one or more steps before the LM transition occurrence. The developed framework has potential to improve the assistance delivered by locomotion assistive devices to achieve a more natural and smooth motion assistance.This work has been supported in part by the Fundação para a Ciência e Tecnologia (FCT) with the Reference Scholarship under Grant SFRH/BD/108309/2015, and part by the FEDER Funds through the Programa Operacional Regional do Norte and national funds from FCT with the project SmartOs -Controlo Inteligente de um Sistema Ortótico Ativo e Autónomo- under Grant NORTE-01-0145-FEDER-030386, and by the FEDER Funds through the COMPETE 2020—Programa Operacional Competitividade e Internacionalização (POCI)—with the Reference Project under Grant POCI-01-0145-FEDER-006941

Desert RHex Technical Report: Jornada and White Sands Trip

Researchers in a variety of fields, including aeolian science, biology, and environmental science, have already made use of stationary and mobile remote sensing equipment to increase their variety of data collection opportunities. However, due to mobility challenges, remote sensing opportunities relevant to desert environments and in particular dune fields have been limited to stationary equipment. We describe here an investigative trip to two well-studied experimental deserts in New Mexico with D-RHex, a mobile remote sensing platform oriented towards desert research. D-RHex is the latest iteration of the RHex family of robots, which are six-legged, biologically inspired, small (10kg) platforms with good mobility in a variety of rough terrains, including on inclines and over obstacles of higher than robot hip height. For more information: Kod*La

The NASA SBIR product catalog

The purpose of this catalog is to assist small business firms in making the community aware of products emerging from their efforts in the Small Business Innovation Research (SBIR) program. It contains descriptions of some products that have advanced into Phase 3 and others that are identified as prospective products. Both lists of products in this catalog are based on information supplied by NASA SBIR contractors in responding to an invitation to be represented in this document. Generally, all products suggested by the small firms were included in order to meet the goals of information exchange for SBIR results. Of the 444 SBIR contractors NASA queried, 137 provided information on 219 products. The catalog presents the product information in the technology areas listed in the table of contents. Within each area, the products are listed in alphabetical order by product name and are given identifying numbers. Also included is an alphabetical listing of the companies that have products described. This listing cross-references the product list and provides information on the business activity of each firm. In addition, there are three indexes: one a list of firms by states, one that lists the products according to NASA Centers that managed the SBIR projects, and one that lists the products by the relevant Technical Topics utilized in NASA's annual program solicitation under which each SBIR project was selected