Actuation system modelling and design optimization for an assistive exoskeleton for disabled and elderly with series and parallel elasticity.

BACKGROUND: The aim of a robotic exoskeleton is to match the torque and angular profile of a healthy human subject in performing activities of daily living. Power and mass are the main requirements considered in the robotic exoskeletons that need to be reduced so that portable designs to perform independent activities by the elderly users could be adopted. OBJECTIVE: This paper evaluates a systematic approach for the design optimization strategies of elastic elements and implements an actuator design solution for an ideal combination of components of an elastic actuation system while providing the same level of support to the elderly. METHODS: A multi-factor optimization technique was used to determine the optimum stiffness and engagement angle of the spring within its elastic limits at the hip, knee and ankle joints. An actuator design framework was developed for the elderly users to match the torque-angle characteristics of the healthy human with the best motor and transmission system combined with series or parallel elasticity in an elastic actuator. RESULTS: With the optimized spring stiffness, a parallel elastic element significantly reduced the torque and power requirements up to 90% for some manoeuvres for the users to perform ADL. When compared with the rigid actuation system, the optimized robotic exoskeleton actuation system reduced the power consumption of up to 52% using elastic elements. CONCLUSION: A lightweight, smaller design of an elastic actuation system consuming less power as compared to a rigid system was realized using this approach. This will help to reduce the battery size and hence the portability of the system could be better adopted to support elderly users in performing daily living activities. It was established that parallel elastic actuators (PEA) can reduce the torque and power better than series elastic actuators (SEA) in performing everyday tasks for the elderly.

Cardiac X-ray image-based haptic guidance for robot-assisted coronary intervention: a feasibility study.

PURPOSE: Effective and efficient haptic guidance is desirable for tele-operated robotic surgery because it has a potential to enhance surgeon's skills, especially in coronary interventions where surgeon loses both an eye-hand coordination and a direct sight to the organ. This paper proposes a novel haptic guidance procedure-both kinesthetic and cutaneous, which solely depends upon X-ray images, for tele-robotic system that assists an efficient navigation of the guidewire towards the target location during a coronary intervention. METHODS: Proposed methodology requires cardiologists to draw virtual fixtures (VFs) on angiograms as a preoperative procedure. During an operation, these VFs direct the guidewire to the desired coronary vessel. For this, the position and orientation of guidewire tip are calculated with respect to VFs' anatomy, using image processing on the real-time 2D fluoroscopic images. The haptic feedbacks are then rendered on to the master device depending on the interaction with attractive and repulsive, guidance and forbidden region VFs. RESULTS: A feasibility study in the laboratory environment is performed by using a webcam as an image acquisition device and a phantom-based coronary vessel model. The subsequent statistical analysis shows that, on an average, a decrease of approx. 37% in task completion time is observed with haptic feedback. Moreover, haptic guidance is found effective for most difficult branch, whereas there is a minimal significance of such haptics for the easiest branch. CONCLUSIONS: The proposed haptic guidance procedure may assist cardiologists for an efficient and effective guidewire navigation during a surgical procedure. The cutaneous haptics (vibration feedback) is found more helpful in coronary interventions compared with kinesthetic haptics (force feedback).

An Overview of Signal Processing Techniques for Remote Health Monitoring Using Impulse Radio UWB Transceiver.

Non-invasive remote health monitoring plays a vital role in epidemiological situations such as SARS outbreak (2003), MERS (2015) and the recently ongoing outbreak of COVID-19 because it is extremely risky to get close to the patient due to the spread of contagious infections. Non-invasive monitoring is also extremely necessary in situations where it is difficult to use complicated wired connections, such as ECG monitoring for infants, burn victims or during rescue missions when people are buried during building collapses/earthquakes. Due to the unique characteristics such as higher penetration capabilities, extremely precise ranging, low power requirement, low cost, simple hardware and robustness to multipath interferences, Impulse Radio Ultra Wideband (IR-UWB) technology is appropriate for non-invasive medical applications. IR-UWB sensors detect the macro as well as micro movement inside the human body due to its fine range resolution. The two vital signs, i.e., respiration rate and heart rate, can be measured by IR-UWB radar by measuring the change in the magnitude of signal due to displacement caused by human lungs, heart during respiration and heart beating. This paper reviews recent advances in IR- UWB radar sensor design for healthcare, such as vital signs measurements of a stationary human, vitals of a non-stationary human, vital signs of people in a vehicle, through the wall vitals measurement, neonate's health monitoring, fall detection, sleep monitoring and medical imaging. Although we have covered many topics related to health monitoring using IR-UWB, this paper is mainly focused on signal processing techniques for measurement of vital signs, i.e., respiration and heart rate monitoring.

A review of gait disorders in the elderly and neurological patients for robot-assisted training.

Purpose: Ambulation is an important objective for people with pathological gaits. Exoskeleton robots can assist these people to complete their activities of daily living. There are exoskeletons that have been presented in literature to assist the elderly and other pathological gait users. This article presents a review of the degree of support required in the elderly and neurological gait disorders found in the human population. This will help to advance the design of robot-assisted devices based on the needs of the end users.Methods: The articles included in this review are collected from different databases including Science Direct, Springer Link, Web of Science, Medline and PubMed and with the purpose to investigate the gait parameters of elderly and neurological patients. Studies were included after considering the full texts and only those which focus on spatiotemporal, kinematic and kinetic gait parameters were selected as they are most relevant to the scope of this review. A systematic review and meta-analysis were conducted.Results: The meta-analysis report on the spatiotemporal, kinematic and kinetic gait parameters of elderly and neurological patients revealed a significant difference based on the type and level of impairment. Healthy elderly population showed deviations in the gait parameters due to age, however, significant difference is observed in the gait parameters of the neurological patients.Conclusion: A level of agreement was observed in most of the studies however the review also noticed some controversies among different studies in the same group. The review on the spatiotemporal, kinematics and kinetic gait parameters will provide a summary of the fundamental needs of the users for the future design and development of robotic assistive devices.Implications for rehabilitationThe support requirements provide the foundation for designing assistive devices.The findings will be crucial in defining the design criteria for robot assistive devices.

Finger-Counting-Based Gesture Recognition within Cars Using Impulse Radar with Convolutional Neural Network.

The diversion of a driver's attention from driving can be catastrophic. Given that conventional button- and touch-based interfaces may distract the driver, developing novel distraction-free interfaces for the various devices present in cars has becomes necessary. Hand gesture recognition may provide an alternative interface inside cars. Given that cars are the targeted application area, we determined the optimal location for the radar sensor, so that the signal reflected from the driver's hand during gesturing is unaffected by interference from the motion of the driver's body or other motions within the car. We implemented a Convolutional Neural Network-based technique to recognize the finger-counting-based hand gestures using an Impulse Radio (IR) radar sensor. The accuracy of the proposed method was sufficiently high for real-world applications.