scholarly journals Wearable Stretch Sensors for Human Movement Monitoring and Fall Detection in Ergonomics

2020 ◽  
Vol 17 (10) ◽  
pp. 3554 ◽  
Author(s):  
Harish Chander ◽  
Reuben F. Burch ◽  
Purva Talegaonkar ◽  
David Saucier ◽  
Tony Luczak ◽  
...  
Keyword(s):  
Human Performance ◽  
Wearable Sensors ◽  
Movement Analysis ◽  
Human Movement ◽  
Fall Detection ◽  
Wearable Technology ◽  
Ongoing Research ◽  
Successful Solution ◽  
Nonfatal Injuries ◽  
Movement Monitoring

Wearable sensors are beneficial for continuous health monitoring, movement analysis, rehabilitation, evaluation of human performance, and for fall detection. Wearable stretch sensors are increasingly being used for human movement monitoring. Additionally, falls are one of the leading causes of both fatal and nonfatal injuries in the workplace. The use of wearable technology in the workplace could be a successful solution for human movement monitoring and fall detection, especially for high fall-risk occupations. This paper provides an in-depth review of different wearable stretch sensors and summarizes the need for wearable technology in the field of ergonomics and the current wearable devices used for fall detection. Additionally, the paper proposes the use of soft-robotic-stretch (SRS) sensors for human movement monitoring and fall detection. This paper also recapitulates the findings of a series of five published manuscripts from ongoing research that are published as Parts I to V of “Closing the Wearable Gap” journal articles that discuss the design and development of a foot and ankle wearable device using SRS sensors that can be used for fall detection. The use of SRS sensors in fall detection, its current limitations, and challenges for adoption in human factors and ergonomics are also discussed.

scholarly journals The Use of Wearable Sensors in Human Movement Analysis in Non-Swimming Aquatic Activities: A Systematic Review

2019 ◽  
Vol 16 (24) ◽  
pp. 5067
Author(s):  
Daniel A. Marinho ◽  
Henrique P. Neiva ◽  
Jorge E. Morais
Keyword(s):  
Systematic Review ◽  
Aquatic Environment ◽  
Web Of Science ◽  
Inertial Sensors ◽  
State Of The Art ◽  
Wearable Sensors ◽  
Movement Analysis ◽  
Human Movement ◽  
Dry Land ◽  
Swimming Kinematics

The use of smart technology, specifically inertial sensors (accelerometers, gyroscopes, and magnetometers), to analyze swimming kinematics is being reported in the literature. However, little is known about the usage/application of such sensors in other human aquatic exercises. As the sensors are getting smaller, less expensive, and simple to deal with (regarding data acquisition), one might consider that its application to a broader range of exercises should be a reality. The aim of this systematic review was to update the state of the art about the framework related to the use of sensors assessing human movement in an aquatic environment, besides swimming. The following databases were used: IEEE Xplore, Pubmed, Science Direct, Scopus, and Web of Science. Five articles published in indexed journals, aiming to assess human exercises/movements in the aquatic environment were reviewed. The data from the five articles was categorized and summarized based on the aim, purpose, participants, sensor’s specifications, body area and variables analyzed, and data analysis and statistics. The analyzed studies aimed to compare the movement/exercise kinematics between environments (i.e., dry land versus aquatic), and in some cases compared healthy to pathological participants. The use of sensors in a rehabilitation/hydrotherapy perspective may provide major advantages for therapists.

scholarly journals Fusion Models for Generalized Classification of Multi-Axial Human Movement: Validation in Sport Performance

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8409
Author(s):  
Rajesh Amerineni ◽  
Lalit Gupta ◽  
Nathan Steadman ◽  
Keshwyn Annauth ◽  
Charles Burr ◽  
...  
Keyword(s):  
Human Performance ◽  
Wearable Sensors ◽  
Human Movement ◽  
Sport Performance ◽  
Time Warping ◽  
Action Classification ◽  
Human Movements ◽  
Non Linear ◽  
Dynamic Time

We introduce a set of input models for fusing information from ensembles of wearable sensors supporting human performance and telemedicine. Veracity is demonstrated in action classification related to sport, specifically strikes in boxing and taekwondo. Four input models, formulated to be compatible with a broad range of classifiers, are introduced and two diverse classifiers, dynamic time warping (DTW) and convolutional neural networks (CNNs) are implemented in conjunction with the input models. Seven classification models fusing information at the input-level, output-level, and a combination of both are formulated. Action classification for 18 boxing punches and 24 taekwondo kicks demonstrate our fusion classifiers outperform the best DTW and CNN uni-axial classifiers. Furthermore, although DTW is ostensibly an ideal choice for human movements experiencing non-linear variations, our results demonstrate deep learning fusion classifiers outperform DTW. This is a novel finding given that CNNs are normally designed for multi-dimensional data and do not specifically compensate for non-linear variations within signal classes. The generalized formulation enables subject-specific movement classification in a feature-blind fashion with trivial computational expense for trained CNNs. A commercial boxing system, ‘Corner’, has been produced for real-world mass-market use based on this investigation providing a basis for future telemedicine translation.

scholarly journals Wearable Skin Sensors and Their Challenges: A Review of Transdermal, Optical, and Mechanical Sensors

Biosensors ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 56 ◽  
Author(s):  
Ammar Ahmad Tarar ◽  
Umair Mohammad ◽  
Soumya K. Srivastava
Keyword(s):  
Large Scale ◽  
Wearable Sensors ◽  
Glucose Monitoring ◽  
Wearable Technology ◽  
The Body ◽  
Ongoing Research ◽  
Existing Problems ◽  
Different Types ◽  
Mechanical Sensors ◽  
Remote Health

Wearable technology and mobile healthcare systems are both increasingly popular solutions to traditional healthcare due to their ease of implementation and cost-effectiveness for remote health monitoring. Recent advances in research, especially the miniaturization of sensors, have significantly contributed to commercializing the wearable technology. Most of the traditional commercially available sensors are either mechanical or optical, but nowadays transdermal microneedles are also being used for micro-sensing such as continuous glucose monitoring. However, there remain certain challenges that need to be addressed before the possibility of large-scale deployment. The biggest challenge faced by all these wearable sensors is our skin, which has an inherent property to resist and protect the body from the outside world. On the other hand, biosensing is not possible without overcoming this resistance. Consequently, understanding the skin structure and its response to different types of sensing is necessary to remove the scientific barriers that are hindering our ability to design more efficient and robust skin sensors. In this article, we review research reports related to three different biosensing modalities that are commonly used along with the challenges faced in their implementation for detection. We believe this review will be of significant use to researchers looking to solve existing problems within the ongoing research in wearable sensors.

scholarly journals Filtering Biomechanical Signals in Movement Analysis

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4580
Author(s):  
Francesco Crenna ◽  
Giovanni Battista Rossi ◽  
Marta Berardengo
Keyword(s):  
Measurement Uncertainty ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Movement Analysis ◽  
Analytical Signal ◽  
Human Movement ◽  
Reference Points ◽  
Biomechanical Analysis ◽  
Method Performance ◽  
Acceleration Signal

Biomechanical analysis of human movement is based on dynamic measurements of reference points on the subject’s body and orientation measurements of body segments. Collected data include positions’ measurement, in a three-dimensional space. Signal enhancement by proper filtering is often recommended. Velocity and acceleration signal must be obtained from position/angular measurement records, needing numerical processing effort. In this paper, we propose a comparative filtering method study procedure, based on measurement uncertainty related parameters’ set, based upon simulated and experimental signals. The final aim is to propose guidelines to optimize dynamic biomechanical measurement, considering the measurement uncertainty contribution due to the processing method. Performance of the considered methods are examined and compared with an analytical signal, considering both stationary and transient conditions. Finally, four experimental test cases are evaluated at best filtering conditions for measurement uncertainty contributions.

scholarly journals Recent Impact of Microfluidics on Skin Models for Perspiration Simulation

Membranes ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 150
Author(s):  
Genís Rabost-Garcia ◽  
Josep Farré-Lladós ◽  
Jasmina Casals-Terré
Keyword(s):  
Sweat Gland ◽  
Ethical Issues ◽  
Wearable Sensors ◽  
Surface Characteristics ◽  
Skin Surface ◽  
Wearable Technology ◽  
Alternative Strategies ◽  
Accurate Model ◽  
Key Features

Skin models offer an in vitro alternative to human trials without their high costs, variability, and ethical issues. Perspiration models, in particular, have gained relevance lately due to the rise of sweat analysis and wearable technology. The predominant approach to replicate the key features of perspiration (sweat gland dimensions, sweat rates, and skin surface characteristics) is to use laser-machined membranes. Although they work effectively, they present some limitations at the time of replicating sweat gland dimensions. Alternative strategies in terms of fabrication and materials have also showed similar challenges. Additional research is necessary to implement a standardized, simple, and accurate model representing sweating for wearable sensors testing.

scholarly journals Lower Limb Kinematics in Individuals with Hip Osteoarthritis during Gait: A Focus on Adaptative Strategies and Interlimb Symmetry

2021 ◽  
Vol 8 (4) ◽  
pp. 47
Author(s):  
Micaela Porta ◽  
Massimiliano Pau ◽  
Bruno Leban ◽  
Michela Deidda ◽  
Marco Sorrentino ◽  
...  
Keyword(s):  
Lower Limb ◽  
Functional Limitations ◽  
Hip Osteoarthritis ◽  
Movement Analysis ◽  
Human Movement ◽  
Point Of View ◽  
Negative Effects ◽  
Gait Patterns ◽  
Limb Kinematics

Among the functional limitations associated with hip osteoarthritis (OA), the alteration of gait capabilities represents one of the most invalidating as it may seriously compromise the quality of life of the affected individual. The use of quantitative techniques for human movement analysis has been found valuable in providing accurate and objective measures of kinematics and kinetics of gait in individuals with hip OA, but few studies have reported in-depth analyses of lower limb joint kinematics during gait and, in particular, there is a scarcity of data on interlimb symmetry. Such aspects were investigated in the present study which tested 11 individuals with hip OA (mean age 68.3 years) and 11 healthy controls age- and sex-matched, using 3D computerized gait analysis to perform point-by-point comparisons of the joint angle trends of hip, knee, and ankle. Angle-angle diagrams (cyclograms) were also built to compute several parameters (i.e., cyclogram area and orientation and Trend Symmetry) from which to assess the degree of interlimb symmetry. The results show that individuals with hip OA exhibit peculiar gait patterns characterized by severe modifications of the physiologic trend at hip level even in the unaffected limb (especially during the stance phase), as well as minor (although significant) alterations at knee and ankle level. The symmetry analysis also revealed that the effect of the disease in terms of interlimb coordination is present at knee joint as well as hip, while the ankle joint appears relatively preserved from specific negative effects from this point of view. The availability of data on such kinematic adaptations may be useful in supporting the design of specific rehabilitative strategies during both preoperative and postoperative periods.

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