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Biomechanics And Motor Control Of Human Movement

In recent years, we have witnessed a rapid surge in assisted living technologies due to a rapidly aging society. The aging population, the increasing cost of formal health care, the caregiver burden, and the importance that the individuals place on living independently, all motivate development of innovative-assisted living technologies for safe and independent aging. In this survey, we will summarize the emergence of `ambient-assisted living” (AAL) tools for older adults based on ambient intelligence paradigm. We will summarize the state-of-the-art AAL technologies, tools, and techniques, and we will look at current and future challenges.

A Survey on Ambient-Assisted Living Tools for Older Adults

Gait analysis using wearable sensors is an inexpensive, convenient, and efficient manner of providing useful information for multiple health-related applications. As a clinical tool applied in the rehabilitation and diagnosis of medical conditions and sport activities, gait analysis using wearable sensors shows great prospects. The current paper reviews available wearable sensors and ambulatory gait analysis methods based on the various wearable sensors. After an introduction of the gait phases, the principles and features of wearable sensors used in gait analysis are provided. The gait analysis methods based on wearable sensors is divided into gait kinematics, gait kinetics, and electromyography. Studies on the current methods are reviewed, and applications in sports, rehabilitation, and clinical diagnosis are summarized separately. With the development of sensor technology and the analysis method, gait analysis using wearable sensors is expected to play an increasingly important role in clinical applications.

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Gait analysis using wearable sensors.

Bio-integrated wearable systems can measure a broad range of biophysical, biochemical, and environmental signals to provide critical insights into overall health status and to quantify human performance. Recent advances in material science, chemical analysis techniques, device designs, and assembly methods form the foundations for a uniquely differentiated type of wearable technology, characterized by noninvasive, intimate integration with the soft, curved, time-dynamic surfaces of the body. This review summarizes the latest advances in this emerging field of “bio-integrated” technologies in a comprehensive manner that connects fundamental developments in chemistry, material science, and engineering with sensing technologies that have the potential for widespread deployment and societal benefit in human health care. An introduction to the chemistries and materials for the active components of these systems contextualizes essential design considerations for sensors and associated platforms that appear in f...

Bio-Integrated Wearable Systems: A Comprehensive Review

This contribution is concerned with joint angle calculation based on inertial measurement data in the context of human motion analysis. Unlike most robotic devices, the human body lacks even surfaces and right angles. Therefore, we focus on methods that avoid assuming certain orientations in which the sensors are mounted with respect to the body segments. After a review of available methods that may cope with this challenge, we present a set of new methods for: (1) joint axis and position identification; and (2) flexion/extension joint angle measurement. In particular, we propose methods that use only gyroscopes and accelerometers and, therefore, do not rely on a homogeneous magnetic field. We provide results from gait trials of a transfemoral amputee in which we compare the inertial measurement unit (IMU)-based methods to an optical 3D motion capture system. Unlike most authors, we place the optical markers on anatomical landmarks instead of attaching them to the IMUs. Root mean square errors of the knee flexion/extension angles are found to be less than 1° on the prosthesis and about 3° on the human leg. For the plantar/dorsiflexion of the ankle, both deviations are about 1°.

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IMU-based joint angle measurement for gait analysis.

Backpacks are common devices that enable people to increase their load carriage capabilities, not only in military missions but also in civilian activities. When heavily loaded, some inadequate load-carriage systems may lead to excessive fatigue or even impair the user. The purpose of the study described here is to increase the understanding of dynamic backpack behaviour and its impact on the user’s performance. Such knowledge can then be used to optimise the design of load carriage systems.

Optimisation of backpack dynamics using gait simulation

Representation of ankle-foot kinematics using an analytical foot rollover model

Prediction of human walking based on simple gait descriptors

Automatic detection of lift-off and touch-down of a pick-up walker using 3D kinematics

Morphological adaptation is a key challenge for Evolutionary Robotics (Bongard, 2013; Doncieux et al., 2015), and robotics in general. Consideration of a robot’s physical form in addition to its control system holds particular promise for imbuing robotic systems with task and environmental adaptability (Sims, 1994; Lipson and Pollack, 2000). The additional degrees of behavioural freedom that can be unlocked when morphology is considered in the evolutionary process allows access to a wide design space, providing a pathway towards resilient, rugged, and adaptable robots that can cope with unforeseen circumstances and be realistically deployed in real-world scenarios (Nygaard et al., 2021b), with corresponding real-world impacts. Morphology evolution allows us to create and study systems based on the principles of embodied cognition, whereby coupling (evolved) controllers to (evolved) physical substrates in a meaningful environment (Miras and Eiben, 2019) allows for surprising, rich behaviours that emerge from interactions between the three (Lehman and Stanley, 2011; Lehman et al., 2020). Embodied cognition provides a route towards improving the complexity and adaptivity of evolved behaviours, leading to a corresponding increase in the applicability of evolutionary robotics systems to challenging scenarios. Systems that can fully exploit the principles of embodied cognition and automatically evolve environment-adapted and task-specific robots is an ambitious and challenging endeavour. To date, evolutionary robotics research is largely conducted on morphologically static robots, mainly due to difficulties in either developing encodings that can effectively navigate the expanded, coupled search space of morphology-plus-controller (Faíña et al., 2013; Cheney et al., 2016), and fabricating/ assessing morphologically adaptable robotic hardware. A recent trend has seen implementations of morphological evolutionary robotics for challenging design domains, which has been shown to be effective in designing robots that are, for example, multi-material, soft (Cheney et al., 2014; Fitzgerald et al., 2021), or physically-embodied (Nygaard et al., 2021a). Emerging technologies offer the opportunity to push the boundaries of possibility for morphology evolution, and numerous recent examples from the literature harness principles including multi-material 3D printing (Howard et al., 2021) and advanced modular systems, alongside frameworks (Eiben and Smith, 2015; Howard et al., 2019) that allow researchers to operate in this rapidly-developing scientific field. This Research Topic called for contributions that illustrate and discuss innovative methods, technologies, software, and philosophical viewpoints that advance the field of evolving robotic morphologies. In the end, the topic accepted 7 original research articles and one mini-review, for a total of 8 accepted articles involving seventeen authors. In Nordmoen et al. , Nordmoen, Veenstra, Ellefsen and Glette compare three different evolutionary algorithms on the challenging task of optimizing morphology-controller pairings for modular robotics. They show that the quality-diversity algorithm MAP-Elites (Mouret and Clune, 2015) finds the highestEdited and reviewed by: A.E. Eiben, VU Amsterdam, Netherlands

David Howard

Papers

Optimisation of backpack dynamics using gait simulation

Representation of ankle-foot kinematics using an analytical foot rollover model

Prediction of human walking based on simple gait descriptors

Automatic detection of lift-off and touch-down of a pick-up walker using 3D kinematics

Editorial: Evolving Robotic Morphologies