Human-activity-centered measurement system:challenges from laboratory to the real environment in assistive gait wearable robotics

Assistive gait wearable robots (AGWR) have shown a great advancement in developing intelligent devices to assist human in their activities of daily living (ADLs). The rapid technological advancement in sensory technology, actuators, materials and computational intelligence has sped up this development process towards more practical and smart AGWR. However, most assistive gait wearable robots are still confined to be controlled, assessed indoor and within laboratory environments, limiting any potential to provide a real assistance and rehabilitation required to humans in the real environments. The gait assessment parameters play an important role not only in evaluating the patient progress and assistive device performance but also in controlling smart self-adaptable AGWR in real-time. The self-adaptable wearable robots must interactively conform to the changing environments and between users to provide optimal functionality and comfort. This paper discusses the performance parameters, such as comfortability, safety, adaptability, and energy consumption, which are required for the development of an intelligent AGWR for outdoor environments. The challenges to measuring the parameters using current systems for data collection and analysis using vision capture and wearable sensors are presented and discussed

Probabilistic identification of sit-to-stand and stand-to-sit with a wearable sensor

Identification of human movements is crucial for the design of intelligent devices capable to provide assistance. In this work, a Bayesian formulation, together with a sequential analysis method, is presented for identification of sit-to-stand (SiSt) and stand-to-sit (StSi) activities. This method performs autonomous iterative accumulation of sensor measurements and decision-making processes, while dealing with noise and uncertainty present in sensors. First, the Bayesian formulation is able to identify sit, transition and stand activity states. Second, the transition state, divided into transition phases, is used to identify the state of the human body during SiSt and StSi. These processes employ acceleration signals from an inertial measurement unit attached to the thigh of participants. Validation of our method with experiments in offline, real-time and a simulated environment, shows its capability to identify the human body during SiSt and StSi with an accuracy of 100% and mean response time of 50 ms (5 sensor measurements). In the simulated environment, our approach shows its potential to interact with low-level methods required for robot control. Overall, this work offers a robust framework for intelligent and autonomous systems, capable to recognise the human intent to rise from and sit on a chair, which is essential to provide accurate and fast assistance

Optimization of the investment casting process

Rapid prototyping is an important technique for manufacturing. This work refers to the manufacture of hollow patterns made of polymeric materials by rapid prototyping technologies for its use in the preparation of ceramic molds in the investment casting process. This work is focused on the development of a process for manufacturing patterns different from those that currently exist due to its hollow interior design, allowing its direct use in the fabrication of ceramic molds; avoiding cracking and fracture during the investment casting process, which is an important process for the foundry industry

Optimiranje postupka kalupljenja u ljevačkom procesu

Rapid prototyping is an important technique for manufacturing. This work refers to the manufacture of hollow patterns made of polymeric materials by rapid prototyping technologies for its use in the preparation of ceramic molds in the investment casting process. This work is focused on the development of a process for manufacturing patterns different from those that currently exist due to its hollow interior design, allowing its direct use in the fabrication of ceramic molds; avoiding cracking and fracture during the investment casting process, which is an important process for the foundry industry.Brzo razvijanje prototipa važna je proizvodna tehnika. Ovaj se rad odnosi na proizvodnju šupljih kalupa izrađenih od polimerskih materijala pomoću tehnologija brzog razvijanja prototipa za uporabu u izradi keramičkih modela u postupku kalupljenja ljevačkog procesa. Ovaj rad je usmjeren na razvijanje postupka za proizvodnju kalupa drukčijih od onih kakvi trenutno postoje i to zbog svoje šuplje unutarnje izvedbe čime se omogućava izravna uporaba u izradi keramičkih modela te se izbje gava pucanje i lom tijekom postupka kalupljenja ljevačkog procesa koji predstavlja važan postupak u ljevaoničkoj industriji

Bayesian perception of touch for control of robot emotion

In this paper, we present a Bayesian approach for perception of touch and control of robot emotion. Touch is an important sensing modality for the development of social robots, and it is used in this work as stimulus through a human-robot interaction. A Bayesian framework is proposed for perception of various types of touch. This method together with a sequential analysis approach allow the robot to accumulate evidence from the interaction with humans to achieve accurate touch perception for adaptable control of robot emotions. Facial expressions are used to represent the emotions of the iCub humanoid. Emotions in the robotic platform, based on facial expressions, are handled by a control architecture that works with the output from the touch perception process. We validate the accuracy of our system with simulated and real robot touch experiments. Results from this work show that our method is suitable and accurate for perception of touch to control robot emotions, which is essential for the development of sociable robots

Evaluation of Gait Transitional phases using Neuromechanical outputs and somatosensory inputs in an Overground walk

In a bipedal walk, the human body experiences continuous changes in stability especially during weight loading and unloading transitions which are reported crucial to avoid fall. Prior stability assessment methods are unclear to quantify stabilities during these gait transitions due to methodological and/or measurement limitations. This study introduces Nyquist and Bode methods to quantify stability gait transitional stabilities using the neuromechanical output (CoP) and somatosensory input (GRF) responses. These methods are implemented for five different walking conditions grouped into walking speed and imitated rotational impairments. The trials were recorded with eleven healthy subjects using motion cameras and force platforms. The time rate of change in O/Is illustrated impulsive responses and modelled in the frequency domain. Nyquist and Bode stability methods are applied to quantify stability margins. Stability margins from outputs illustrated loading phases as stable and unloading phases as unstable in all walking conditions. There was a strong intralimb compensatory interaction (p &lt; .001, Spearman correlation) found between opposite limbs. Overall, both walking groups illustrated a decrease (p &lt; .05, Wilcoxon signed-rank test) in stability margins compared with normal/preferred speed walk. Further, stabilities quantified from outputs were found greater in magnitudes than the instability quantified from inputs illustrating the neuromotor balance control ability. These stability outcomes were also compared by applying extrapolated-CoM method. These methods of investigating gait dynamic stability are considered as having important implications for the assessment of ankle-foot impairments, rehabilitation effectiveness, and wearable orthoses.</p