Application of Social Robots in Healthcare: Review on Characteristics, Requirements, Technical Solutions.

Cyber-physical or virtual systems or devices that are capable of autonomously interacting with human or non-human agents in real environments are referred to as social robots. The primary areas of application for biomedical technology are nursing homes, hospitals, and private homes for the purpose of providing assistance to the elderly, people with disabilities, children, and medical personnel. This review examines the current state-of-the-art of social robots used in healthcare applications, with a particular emphasis on the technical characteristics and requirements of these different types of systems. Humanoids robots, companion robots, and telepresence robots are the three primary categories of devices that are identified and discussed in this article. The research looks at commercial applications, as well as scientific literature (according to the Scopus Elsevier database), patent analysis (using the Espacenet search engine), and more (searched with Google search engine). A variety of devices are enumerated and categorized, and then our discussion and organization of their respective specifications takes place.

Movement Analysis Could Help in the Assessment of Chronic Low Back Pain Patients: Results from a Preliminary Explorative Study.

Introduction: This study aimed to assess the reliability of a qualitative scoring system based on the movement analysis of the spine in different populations and after usual care rehabilitative intervention. If proven true, the results could further future research development in quantitative indexes, leading to a possible subclassification of chronic low back pain (cLBP). Methods: This was a preliminary exploratory observational study. Data of an optoelectronic spine movement analysis from a pathological population (cLBP population, 5 male, 5 female, age 58 ± 16 years) were compared to young healthy participants (5M, 5F, age 22 ± 1) and were analysed via a new qualitative score of the pattern of movement. Internal consistency was calculated. Two independent assessors (experienced and inexperienced) assessed the blinded data, and we calculated inter- and intrarater reliability. We performed an analysis for cLBP pre and post a ten session group rehabilitation program between and within groups. Results: Internal consistency was good for all movements (α = 0.84-0.88). Intra-rater reliability (Intraclass correlation coefficient-ICC) was excellent for overall scores of all movements (ICC(1,k) = 0.95-0.99), while inter-rater reliability was poor to moderate (ICC(1,k) = 0.39-0.78). We found a significant difference in the total movement scores between cLBP and healthy participants (p = 0.001). Within-group comparison (cLBP) showed no significant difference in the total movement score in pre and post-treatment. Conclusion: The perception of differences between normal and pathological movements has been confirmed through the proposed scoring system, which proved to be able to distinguish different populations. This study has many limitations, but these results show that movement analysis could be a useful tool and open the door to quantifying the identified parameters through future studies.

Sensors and Actuation Technologies in Exoskeletons: A Review.

Exoskeletons are robots that closely interact with humans and that are increasingly used for different purposes, such as rehabilitation, assistance in the activities of daily living (ADLs), performance augmentation or as haptic devices. In the last few decades, the research activity on these robots has grown exponentially, and sensors and actuation technologies are two fundamental research themes for their development. In this review, an in-depth study of the works related to exoskeletons and specifically to these two main aspects is carried out. A preliminary phase investigates the temporal distribution of scientific publications to capture the interest in studying and developing novel ideas, methods or solutions for exoskeleton design, actuation and sensors. The distribution of the works is also analyzed with respect to the device purpose, body part to which the device is dedicated, operation mode and design methods. Subsequently, actuation and sensing solutions for the exoskeletons described by the studies in literature are analyzed in detail, highlighting the main trends in their development and spread. The results are presented with a schematic approach, and cross analyses among taxonomies are also proposed to emphasize emerging peculiarities.

Intention Prediction and Human Health Condition Detection in Reaching Tasks with Machine Learning Techniques.

Detecting human motion and predicting human intentions by analyzing body signals are challenging but fundamental steps for the implementation of applications presenting human-robot interaction in different contexts, such as robotic rehabilitation in clinical environments, or collaborative robots in industrial fields. Machine learning techniques (MLT) can face the limit of small data amounts, typical of this kind of applications. This paper studies the illustrative case of the reaching movement in 10 healthy subjects and 21 post-stroke patients, comparing the performance of linear discriminant analysis (LDA) and random forest (RF) in: (i) predicting the subject's intention of moving towards a specific direction among a set of possible choices, (ii) detecting if the subject is moving according to a healthy or pathological pattern, and in the case of discriminating the damage location (left or right hemisphere). Data were captured with wearable electromagnetic sensors, and a sub-section of the acquired signals was required for the analyses. The possibility of detecting with which arm (left or right hand) the motion was performed, and the sensitivity of the MLT to variations in the length of the signal sub-section were also evaluated. LDA and RF prediction accuracies were compared: Accuracy improves when only healthy subjects or longer signals portions are considered up to 11% and at least 10%, respectively. RF reveals better estimation performance both as intention predictor (on average 59.91% versus the 62.19% of LDA), and health condition detector (over 90% in all the tests).

Quantitative analysis of voluntary movement and anticipatory postural adjustments: a functional approach.

Daily living activities and tasks like standing forward reaching present complex Anticipatory Postural Adjustments (APAs), and an objective, repeatable, subject- and task-dependent procedure to detect Voluntary Movements (VM) and APAs onsets is still missing. This paper proposes a new approach to the VMs study, based on a functional mechanical interpretation of the movement performing, which allows defining kinematic and dynamic APAs. A protocol for the identification of VMs and APAs onsets in the reaching movement is presented. Acquired data on 9 healthy young subjects enable a preliminary validation of this method suitability as support for an objective quantification of APAs.

The Robot Selection Problem for Mini-Parallel Kinematic Machines: A Task-Driven Approach to the Selection Attributes Identification.

In the last decades, the Robot Selection Problem (RSP) has been widely investigated, and the importance of properly structuring the decision problem has been stated. Crucial aspect in this process is the correct identification of the robot attributes, which should be limited in number as much as possible, but should be also able to detect at best the peculiar requirements of specific applications. Literature describes several attributes examples, but mainly dedicated to traditional industrial tasks, and applied to the selection of conventional industrial robots. After a synthetic review of the robot attributes depicted in the RSP literature, presented with a custom taxonomy, this paper proposes a set of possible requirements for the selection problem of small scale parallel kinematic machines (PKMs). The RSP is based on a task-driven approach: two mini-manipulators are compared as equivalent linear actuators to be integrated within a more complex system, for the application in both an industrial and a biomedical environment. The set of identified criteria for the two environments is proposed in the results and investigated with respect to working conditions and context in the discussion, emphasizing limits and strength points of this approach; finally, the conclusions synthesizes the main results.

Dual Control for Jerk-Driven Robotics in Rehabilitative Planar Applications.

This study compares a set of strategies to plan and control the trajectory of a robotic device in a planar workspace. These strategies are based on an affective application of jerk-laws able to indicate undesirable conditions (e.g., vibrations) facilitating the device control. The jerk is the time derivative of acceleration, and this solution provides an indirect means to control the variation rate of the actuator torques, while avoiding the complex robot dynamic models and their algorithms for computing the dynamics. In order to obtain a smooth trajectory, a regulator to control a robotic device has been developed and validated. It consists of the implementation of two control modules able to i) generate the predefined trajectory and ii) guarantee the path tracking, reducing unwanted effects. In this case a simple S-shaped path has been originated by the "trajectory generator module" as a reference movement to rehabilitate upper limb functionality. The numerical simulation and the results of preliminary tests show the efficacy of the proposed approach through the vibration smoothness appraisal associated with the motion profile.

Trunk motion analysis: a systematic review from a clinical and methodological perspective.

INTRODUCTION: This systematic literature review aims to check the current state of affairs of non-gait-related optoelectronic trunk movement analysis; results have been analyzed from a clinical and a methodological perspective. EVIDENCE ACQUISITION: Extensive research was performed on all papers published until December 31st, 2015, dealing with trunk movement analysis assessed by optoelectronic systems, excluding those related to gait. The research was performed on the 14th of January 2016 on three databases: Scopus, Science Direct and Pubmed. A reference search and expert consultation were also performed. EVIDENCE SYNTHESIS: Out of a total number of 8431 papers, 45 were deemed relevant: they included 1334 participants, 57.9% healthy, with age range 8-85. Few studies considered the whole trunk, and none focused on each vertebra independently: the trunk was almost always divided into three segments. Thirteen studies included 20 or more markers. Most of the papers focused mainly on the biomechanics of various movements; the lumbar area and low back pain were the most studied region and pathology respectively. CONCLUSIONS: This study has shown the relative scarcity of current literature focusing on trunk motion analysis. In clinical terms, results were sparse. The only quite well represented group of papers focused on the lumbar spine and pathologies, but the scarcity of individuals evaluated make the results questionable. The use of optoelectronic systems in the evaluation of spine movement is a growing research area. Nevertheless, no standard protocols have been developed so far. Future research is needed to define a precise protocol in terms of number and position of markers along the spine and movements and tasks to be evaluated.

[Bioelectric prostheses: review of classifications and control strategies]. / Bioelectric prostheses: review of classifications and control strategies.

Bioelectric prosthesis are those mechatronical devices able to substitute the total or partial loss of a limb or a system, and controlled by the patient thanks to wilful bioelectric signals, such as muscular contractions (electromyographic signals, EMG) or activation of specific encephalic areas (which can be revealed by encephalogram, EEG). At the end of an analysis of the devices currently in literature and on the market, the present paper collects and synthesize the possible classification strategies of these prosthetic devices, paying particular attention also to the classification obtained by possible control strategies of the prosthesis. This summary aims to support and sustain physicians and patients along the identification of the most appropriate prosthesis, for the specific subject, the choice of the "optimal" device, must consider also patient needs and expectations, possible pathological constraints and technological complexity of the system. This paper presents, after a brief theoretical introduction about the background, a short description of materials and methods implemented in order to identify classification typologies; the main results, collected in 2 tables, will be then described, and commented highlighting advantages and limbs of the proposed classifications.