The kinectome: a comprehensive kinematic map of human motion in health and disease

Effective human movement requires the coordinated participation of the whole musculoskeletal system. Here we propose to represent the human body movements as a network (that we named "kinectome"), where nodes are body parts, and edges are defined as the correlations of the accelerations between each pair of body parts during gait. We apply this framework in healthy individuals and patients with Parkinson's disease (PD). The network dynamics in Parkinson's display high variability, as conveyed by the high variance and the modular structure in the patients' kinectomes. Furthermore, our analysis identified a set of anatomical elements that are specifically related to the balance impairment in PD. Furthermore, each participant could be identified basedon its kinectome patterns, akin to a "fingerprint" of movement, confirming that our approach captures relevant features of gait. We hope that applying network approaches to human kinematics yields new insights to characterize human movement.

Wearable Detection of Trunk Flexions: Capacitive Elastomeric Sensors Compared to Inertial Sensors

Continuous monitoring of flexions of the trunk via wearable sensors could help various types of workers to reduce risks associated with incorrect postures and movements. Stretchable piezo-capacitive elastomeric sensors based on dielectric elastomers have recently been described as a wearable, lightweight and cost-effective technology to monitor human kinematics. Their stretching causes an increase of capacitance, which can be related to angular movements. Here, we describe a wearable wireless system to detect flexions of the trunk, based on such sensors. In particular, we present: (i) a comparison of different calibration strategies for the capacitive sensors, using either an accelerometer or a gyroscope as an inclinometer; (ii) a comparison of the capacitive sensors’ performance with those of the accelerometer and gyroscope; to that aim, the three types of sensors were evaluated relative to stereophotogrammetry. Compared to the gyroscope, the capacitive sensors showed a higher accuracy. Compared to the accelerometer, their performance was lower when used as quasi-static inclinometers but also higher in case of highly dynamic accelerations. This makes the capacitive sensors attractive as a complementary, rather than alternative, technology to inertial sensors.

A Real-Time Photogrammetric System for Acquisition and Monitoring of Three-Dimensional Human Body Kinematics

Real-time acquisition and analysis of three-dimensional (3D) human body kinematics are essential in many applications. In this paper, we present a real-time photogrammetric system consisting of a stereo pair of red-green-blue (RGB) cameras. The system incorporates a multi-threaded and graphics processing unit (GPU)-accelerated solution for real-time extraction of 3D human kinematics. A deep learning approach is adopted to automatically extract two-dimensional (2D) human body features, which are then converted to 3D features based on photogrammetric processing, including dense image matching and triangulation. The multi-threading scheme and GPU-acceleration enable real-time acquisition and monitoring of 3D human body kinematics. Experimental analysis verified that the system processing rate reached ∼18 frames per second. The effective detection distance reached 15 m, with a geometric accuracy of better than 1% of the distance within a range of 12 m. The real-time measurement accuracy for human body kinematics ranged from 0.8% to 7.5%. The results suggest that the proposed system is capable of real-time acquisition and monitoring of 3D human kinematics with favorable performance, showing great potential for various applications.

Lower limb rehabilitation exoskeleton robot: A review

Lower limb rehabilitation exoskeleton robots (LLRERs) play a positive role in lower limb rehabilitation and assistance for patients with lower limb disorders, and they are helpful to improve patients’ physical status. More and more experiments pay more attention to the kinematic and dynamic data characteristics of different patient groups. However, it is not clear whether these devices have broad adaptability and their clinical significance, so it is necessary to summarize and analyze these research results. This paper summarizes the LLRERs prototype and product in recent years, also compares the advantages and disadvantages of the theory and technology used in these research, and compares the functional characteristics of the devices, finally summarizes the aspects of the LLRERs to be improved. These devices apply advanced theories, techniques or structures, as well as human kinematics and dynamics data. However, due to the complexity of human body characteristics and movement rules, the theory or technology applied in the study design of LLRERs remains to be further studied, which can be improved in many aspects, such as improve the human-computer cooperation of equipment or carry out clinical trials. This paper can provide reference for researchers and designers in the future study, as well as understanding and selecting LLRERs for all kinds of therapist and patients.

Calibration Algorithm for MIMU Sensors Group

Non-optical wearable sensors, such as magnetic and inertial measuring units (MIMU), are becoming popular in various fields: sports, medical, industrial - due to their ease of use and relative availability. We propose an algorithm for calibrating wearable sensors based on the rotation algebra. A system for visualizing human kinematics, which is reconstructed from MIMUs' data, is presented.

Assessment of hand function during activities of daily living using motion tracking cameras: A systematic review

The human hand is the most frequently used body part in activities of daily living. With its complex anatomical structure and the small size compared to the body, assessing the functional capability is highly challenging. The aim of this review was to provide a systematic overview on currently available 3D motion analysis based on skin markers for the assessment of hand function during activities of daily living. It is focused on methodology rather than results. A systematic review according to the PRISMA guidelines was performed. The systematic search yielded 1349 discrete articles. Of 147 articles included on basis of title, 123 were excluded after abstract review, and 24 were included in the full-text analysis with 13 key articles. There is still limited knowledge about hand and finger kinematics during activities of daily living. A standardization of the task is required in order to overcome the nonrepetitive nature and high variability of upper limb motion and ensure repeatability of task performance. To yield a progress in the analysis of human hand movements, an assessment of human kinematics including fingers, wrist, and thumb and an identification of relevant parameters that characterize a healthy motion pattern during functional tasks are needed.