Inertial measurement units: a brief state of the art on gait analysis

Gait analysis systems are monitoring systems that establish a symbiosis relationship with Ambient Assisted Living (AAL) environments. Human locomotion analysis has a very important role always aiming at improving the quality of life both for individuals needing treatment or rehabilitation, as well as for healthy and elderly people. In fact, a deep and detailed knowledge about gait characteristics at a given time, and not least, monitoring and evaluating over time, will allow early diagnosis of diseases and their complications, and contribute to the decision of the treatment that should be chosen. There are several techniques used for gait measuring such as: Image Processing, Floor Sensors, and Wearable Sensors. Among the wearable sensors, has emerged an electronic device that combines multiple sensors designated by Inertial Measurement Unit (IMU). This device measures angular rate, body's specific force, and in some cases the magnetic field, and this information may be used to monitor human gait. In this article, the aim is: i) to verify the sensors that build up the IMUs, and the resulting designations that the device may have depending on the sensors it contains; ii) to list the applications of the IMUs on gait analysis; iii) to be aware of the devices available on the market and the associated commercial brands; and iv) to list the advantages and disadvantages associated with the device compared to other gait analysis systems. Concerning the literature in the scientific community, although there are some studies that focus on gait analysis or IMUs, none of them aggregates the purposes that will be addressed in this article.This work is supported by the FCT - Fundação para a Ciência e Tecnologia - with the scholarship reference SFRH/BD/108309/2015, with the reference project UID/EEA/04436/2013, by FEDER funds through the COMPETE 2020 - Programa Operacional Competitividade e Internacionalização (POCI) - with the reference project POCI-01-0145- FEDER-006941

Low power glove for hand functioning analysis in children with cerebral palsy

In this paper, a low-cost glove has been manufactured to monitor and analyse the hand motion for the children who suffer from the cerebral palsy. Cerebral palsy (CP) is a combination of continual disorders affect the movement’s evolution due to a non-gradual disturbance in developing fetal or infant cerebrum. An Arduino Nano microcontroller with flex and force sensors are attached to soft cloth glove to form the analysis glove. The data of this study is collected from children who have cerebral palsy, non-cerebral palsy, and children who are treating by physiotherapy and then compared with each other. The results show that the analysis glove helps the physiotherapist to assess the hand functioning problem such as difficulty in hand grip and inability to fully bend the hand figures in general and thumb figure in particular. These remarks can help physiotherapists to define the required program to improve these functions and indications

Objective assessment of movement disabilities using wearable sensors

The research presents a series of comprehensive analyses based on inertial measurements obtained from wearable sensors to quantitatively describe and assess human kinematic performance in certain tasks that are most related to daily life activities. This is not only a direct application of human movement analysis but also very pivotal in assessing the progression of patients undergoing rehabilitation services. Moreover, the detailed analysis will provide clinicians with greater insights to capture movement disorders and unique ataxic features regarding axial abnormalities which are not directly observed by the clinicians

Hum Factors

Objective:To gather information on the (a) types of wearable sensors, particularly personal activity monitors, currently used by occupational safety and health (OSH) professionals, (b) potential benefits of using such technologies in the workplace, and (c) perceived barriers preventing the widespread adoption of wearable sensors in industry.Background:Wearable sensors are increasingly being promoted as a means to improve employee health and well-being and there is mounting evidence supporting their use as exposure assessment and personal health tools. Despite this, many workplaces have been hesitant to adopt these technologies.Methods:An electronic survey was emailed to 28,428 registered members of the American Society of Safety Engineers (ASSE) and 1,302 professionals certified by the Board of Certification in Professional Ergonomics (BCPE).Results:A total of 952 valid responses were returned. Over half of respondents described being in favor of using wearable sensors to track OSH-related risk factors and relevant exposure metrics at their respective workplaces. However, barriers including concerns regarding employee privacy/confidentiality of collected data, employee compliance, sensor durability, the cost/benefit ratio of using wearables, and good manufacturing practice requirements were described as challenges precluding adoption.Conclusion:The broad adoption of wearable technologies appears to depend largely on the scientific community\u2019s ability to successfully address the identified barriers.Application:Investigators may use the information provided to develop research studies that better address OSH practitioner concerns and that help technology developers operationalize wearable sensors to improve employee health and well-being.T42 OH008436/OH/NIOSH CDC HHSUnited States/2022-07-22T00:00:00Z29320232PMC930713011686vault:4300

Accuracy and repeatability of wrist joint angles in boxing using an electromagnetic tracking system

© 2019, The Author(s). The hand-wrist region is reported as the most common injury site in boxing. Boxers are at risk due to the amount of wrist motions when impacting training equipment or their opponents, yet we know relatively little about these motions. This paper describes a new method for quantifying wrist motion in boxing using an electromagnetic tracking system. Surrogate testing procedure utilising a polyamide hand and forearm shape, and in vivo testing procedure utilising 29 elite boxers, were used to assess the accuracy and repeatability of the system. 2D kinematic analysis was used to calculate wrist angles using photogrammetry, whilst the data from the electromagnetic tracking system was processed with visual 3D software. The electromagnetic tracking system agreed with the video-based system (paired t tests) in both the surrogate ( 0.9). In the punch testing, for both repeated jab and hook shots, the electromagnetic tracking system showed good reliability (ICCs > 0.8) and substantial reliability (ICCs > 0.6) for flexion–extension and radial-ulnar deviation angles, respectively. The results indicate that wrist kinematics during punching activities can be measured using an electromagnetic tracking system

A hybrid modified group method of data handling with the wavelet decomposition for oil palm price forecasting

This thesis presents an exploratory study on hybrid modelling of palm oil price forecasting using modified group method of data handling (GMDH) network with the discrete wavelet transform (DWT) approach. Despite the fact that Malaysia is one of the largest producer and exporter of palm oil, the research on modelling of palm oil price forecasting is still in progress. This study comprises by exploring the appropriate models for forecasting the monthly palm oil price such as conventional GMDH, modified GMDH and hybrid wavelet modified GMDH models. To assess the effectiveness of these models, monthly crude palm oil (CPO) price of Malaysia from January 1983 until November 2019 and Pakistan from September 2001 until June 2019 were used as sample study. The study shows that modified GMDH model, which integrates four transfer functions such as radial basis, sigmoid, tangent and polynomial simultaneously into GMDH, has given the best fit for modelling of palm oil price forecasting as compared to conventional GMDH model. However, the individual model is not best every time to achieve the better results. In improving the model, this study explores a hybrid wavelet modified GMDH model. The architecture of the proposed hybrid model includes DWT, which is selected as a preprocessed clean and pure data enabling the modified GMDH network to present itself as a well-established alternative application to predict the future of CPO. The proposed hybrid model has been applied to different CPO data sets and verified using simulation of different splits of model input data series. Comparative studies among various models were carried out. The mean absolute percentage error (MAPE) of the proposed hybrid model for the monthly CPO price of Malaysia is less than 4 % and coefficient of correlation (R) is 0.99, which show an excellent fit as compared to the individual and other benchmark models. Similarly, the MAPE of hybrid model for Pakistan imports monthly CPO is less than 14 % and R is 0.94, which show good fit as compared to the individual and other benchmark models. The results have demonstrated that the proposed hybrid model is a better alternative model for crude palm oil price forecastin

Exploring the role of wearable technology in sport kinematics and kinetics: a systematic review

The aim of this review was to understand the use of wearable technology in sport in order to enhance performance and prevent injury. Understanding sports biomechanics is important for injury prevention and performance enhancement and is traditionally assessed using optical motion capture. However, such approaches are limited by capture volume restricting assessment to a laboratory environment, a factor that can be overcome by wearable technology. A systematic search was carried out across seven databases where wearable technology was employed to assess kinetic and kinematic variables in sport. Articles were excluded if they focused on sensor design and did not measure kinetic or kinematic variables or apply the technology on targeted participants. A total of 33 articles were included for full-text analysis where participants took part in a sport and performed dynamic movements relating to performance monitored by wearable technologies. Inertial measurement units, flex sensors and magnetic field and angular rate sensors were among the devices used in over 15 sports to quantify motion. Wearable technology usage is still in an exploratory phase, but there is potential for this technology to positively influence coaching practice and athletes’ technique

Low-cost real-time motion capturing system using inertial measurement units

Human movement modeling - also referred to as motion-capture - is a rapidly expanding field of interest for medical rehabilitation, sports training, and entertainment. Motion capture devices are used to provide a virtual 3-dimensional reconstruction of human physical activities - employing either optical or inertial sensors. Utilizing inertial measurement units and digital signal processing techniques offers a better alternative in terms of portability and immunity to visual perturbations when compared to conventional optical solutions. In this paper, a cable-free, low-cost motion-capture solution based on inertial measurement units with a novel approach for calibration is proposed. The goal of the proposed solution is to apply motion capture to the fields that, because of cost problems, did not take enough benefit of such technology (e.g., fitness training centers). According to this goal, the necessary requirement for the proposed system is to be low-cost. Therefore, all the considerations and all the solutions provided in this work have been done according to this main requirement