Special Issue "Human Health Engineering"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".

Deadline for manuscript submissions: closed (20 July 2019).

Special Issue Editor

Guest Editor
Dr. Jean Marie Aerts

KU Leuven, Division Animal and Human Health Engineering, 3000 Leuven, Belgium
Website | E-Mail
Interests: human health engineering, wearable technology, data-based modelling

Special Issue Information

Dear Colleagues,

Thanks to the (r)evolution in sensors and sensing systems (wearable, wireless, micro-/nanoscale), computing power (ubiquitous computing) and algorithms (real-time modelling, neural computing, deep learning, etc.) a lot of (wearable) technology is being developed for monitoring health status of individuals in real-time. The wearable technology developed in the field of Human Health Engineering is not only aimed at patients but also at healthy people. Application areas include, but are not limited to, patient monitoring in hospital settings, (chronically ill) patient home monitoring, depression monitoring, stress monitoring at work, drowsiness monitoring of car drivers, monitoring of physical condition of athletes, activity monitoring of elderly people, etc.

In this Special Issue, we invite submissions exploring the development of technology for monitoring the physical or mental status of individuals in a variety of applications. Contributions can focus on sensors, wearable hardware, algorithms, or integrated monitoring systems. Survey papers and reviews are also welcomed.

Dr. Jean Marie Aerts
Guest Editor

Manuscript Submission Information

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Keywords

  • human health engineering
  • physical and mental health monitoring
  • wearable technology
  • real-time monitoring algorithms
  • sensors
  • wearable hardware

Published Papers (17 papers)

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Research

Open AccessArticle
Development of the Dyskinesia Impairment Mobility Scale to Measure Presence and Severity of Dystonia and Choreoathetosis during Powered Mobility in Dyskinetic Cerebral Palsy
Appl. Sci. 2019, 9(17), 3481; https://doi.org/10.3390/app9173481 (registering DOI)
Received: 20 July 2019 / Revised: 17 August 2019 / Accepted: 20 August 2019 / Published: 23 August 2019
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Abstract
The majority of individuals with dyskinetic cerebral palsy cannot use powered mobility with a joystick, due to the lack of manual abilities by the severe presence of dystonia and choreoathetosis. Reliable measurements of these movement disorders is indispensable for good evaluation towards evidence–based [...] Read more.
The majority of individuals with dyskinetic cerebral palsy cannot use powered mobility with a joystick, due to the lack of manual abilities by the severe presence of dystonia and choreoathetosis. Reliable measurements of these movement disorders is indispensable for good evaluation towards evidence–based insights during powered mobility. This study aimed to develop and assess the Dyskinesia Impairment Mobility Scale (DIMS), a video–based tool to measure presence and severity of dystonia and choreoathetosis during powered mobility. DIMS was measured for the neck and arms region during five mobility tasks. Interrater reliability, test–retest reliability, internal consistency and concurrent validity of the DIMS were assessed. Interrater reliability coefficients ranged between 0.68 and 0.87 for the total DIMS, and the dystonia and choreoathetosis subscales. Test–retest reliability was moderate to excellent (range 0.51–0.93) while Cronbach’s alpha was good (range 0.69–0.81) for the total scale and subscale scores. Concurrent validity showed during mobility tasks significant correlations with rest postures in the arm region, and with requested but voluntary activity in the neck region. The DIMS reliably measures the presence and severity of the movement disorders during powered mobility, increasing insights into the underlying mechanisms of independent mobility. This scale may therefore be a promising tool to evaluate mobility training. Full article
(This article belongs to the Special Issue Human Health Engineering)
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Open AccessArticle
Reverse Engineering of Thermoregulatory Cold-Induced Vasoconstriction/Vasodilation during Localized Cooling
Appl. Sci. 2019, 9(16), 3372; https://doi.org/10.3390/app9163372
Received: 10 July 2019 / Revised: 2 August 2019 / Accepted: 8 August 2019 / Published: 16 August 2019
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Abstract
Biological systems, in general, represent a special type of control system. The physiological processes of homeostasis, which serve to maintain the organism’s internal equilibrium against external influences, are clear forms of biological control system. An example of the homeostasis is the control of [...] Read more.
Biological systems, in general, represent a special type of control system. The physiological processes of homeostasis, which serve to maintain the organism’s internal equilibrium against external influences, are clear forms of biological control system. An example of the homeostasis is the control of the organism thermal state or the thermoregulation. The thermoregulatory control of human skin blood flow, via vasoconstriction and vasodilation, is vital to maintaining normal body temperatures during challenges to thermal homeostasis such as localised cooling. The main objective of this paper is to reverse engineer the localised thermoregulatory cold-induced vasoconstriction/vasodilation (CIVC/CIVD) reactions using a data-based mechanistic approach. Two types of localised cooling were applied to the fingers of 33 healthy participants, namely, continuous and intermittent cooling. Modelling of the thermoregulatory cold-induced vasoconstriction/vasodilation reactions suggested two underlying processes, with one process being 10 times faster. A new term is suggested in this paper, namely, the latent heat of CIVD, which represents the amount of dissipated heat required to trigger the CIVD. Moreover, a new model for the thermoregulatory localised CIVC/CIVD reactions is proposed. The suggested new model states that, with an initial vasodilation state, the initial localised CIVC is triggered based on a certain threshold in the rate of heat dissipation from the skin to the surrounding environment. Full article
(This article belongs to the Special Issue Human Health Engineering)
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Open AccessArticle
Towards Online Personalized-Monitoring of Human Thermal Sensation Using Machine Learning Approach
Appl. Sci. 2019, 9(16), 3303; https://doi.org/10.3390/app9163303
Received: 20 July 2019 / Revised: 31 July 2019 / Accepted: 2 August 2019 / Published: 12 August 2019
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Abstract
Thermal comfort and sensation are important aspects of building design and indoor climate control, as modern man spends most of the day indoors. Conventional indoor climate design and control approaches are based on static thermal comfort/sensation models that view the building occupants as [...] Read more.
Thermal comfort and sensation are important aspects of building design and indoor climate control, as modern man spends most of the day indoors. Conventional indoor climate design and control approaches are based on static thermal comfort/sensation models that view the building occupants as passive recipients of their thermal environment. To overcome the disadvantages of static models, adaptive thermal comfort models aim to provide opportunity for personalized climate control and thermal comfort enhancement. Recent advances in wearable technologies contributed to new possibilities in controlling and monitoring health conditions and human wellbeing in daily life. The generated streaming data generated from wearable sensors are providing a unique opportunity to develop a real-time monitor of an individual’s thermal state. The main goal of this work is to introduce a personalized adaptive model to predict individual’s thermal sensation based on non-intrusive and easily measured variables, which could be obtained from already available wearable sensors. In this paper, a personalized classification model for individual thermal sensation with a reduced-dimension input-space, including 12 features extracted from easily measured variables, which are obtained from wearable sensors, was developed using least-squares support vector machine algorithm. The developed classification model predicted the individual’s thermal sensation with an overall average accuracy of 86%. Additionally, we introduced the main framework of streaming algorithm for personalized classification model to predict an individual’s thermal sensation based on streaming data obtained from wearable sensors. Full article
(This article belongs to the Special Issue Human Health Engineering)
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Open AccessArticle
Towards Model-Based Online Monitoring of Cyclist’s Head Thermal Comfort: Smart Helmet Concept and Prototype
Appl. Sci. 2019, 9(15), 3170; https://doi.org/10.3390/app9153170
Received: 10 July 2019 / Revised: 29 July 2019 / Accepted: 1 August 2019 / Published: 4 August 2019
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Abstract
Bicyclists can be subjected to crashes, which can cause injuries over the whole body, especially the head. Head injuries can be prevented by wearing bicycle helmets; however, bicycle helmets are frequently not worn due to a variety of reasons. One of the most [...] Read more.
Bicyclists can be subjected to crashes, which can cause injuries over the whole body, especially the head. Head injuries can be prevented by wearing bicycle helmets; however, bicycle helmets are frequently not worn due to a variety of reasons. One of the most common complaints about wearing bicycle helmets relates to thermal discomfort. So far, insufficient attention has been given to the thermal performance of helmets. This paper aimed to introduce and develop an adaptive model for the online monitoring of head thermal comfort based on easily measured variables, which can be measured continuously using impeded sensors in the helmet. During the course of this work, 22 participants in total were subjected to different levels of environmental conditions (air temperature, air velocity, mechanical work and helmet thermal resistance) to develop a general model to predict head thermal comfort. A reduced-order general linear regression model with three input variables, namely, temperature difference between ambient temperature and average under-helmet temperature, cyclist’s heart rate and the interaction between ambient temperature and helmet thermal resistance, was the most suitable to predict the cyclist’s head thermal comfort and showed maximum mean absolute percentage error (MAPE) of 8.4%. Based on the selected model variables, a smart helmet prototype (SmartHelmet) was developed using impeded sensing technology, which was used to validate the developed general model. Finally, we introduced a framework of calculation for an adaptive personalised model to predict head thermal comfort based on streaming data from the SmartHelmet prototype. Full article
(This article belongs to the Special Issue Human Health Engineering)
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Open AccessArticle
Estimating Airway Resistance from Forced Expiration in Spirometry
Appl. Sci. 2019, 9(14), 2842; https://doi.org/10.3390/app9142842
Received: 6 June 2019 / Revised: 2 July 2019 / Accepted: 11 July 2019 / Published: 16 July 2019
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Abstract
Spirometry is the gold standard to detect airflow limitation, but it does not measure airway resistance, which is one of the physiological factors behind airflow limitation. In this study, we describe the dynamics of forced expiration in spirometry using a deflating balloon and [...] Read more.
Spirometry is the gold standard to detect airflow limitation, but it does not measure airway resistance, which is one of the physiological factors behind airflow limitation. In this study, we describe the dynamics of forced expiration in spirometry using a deflating balloon and using this model. We propose a methodology to estimate ζ (zeta), a dimensionless and effort-independent parameter quantifying airway resistance. In N = 462 (65 ± 8 years), we showed that ζ is significantly (p < 0.0001) greater in COPD (2.59 ± 0.99) than healthy smokers (1.64 ± 0.18), it increased significantly (p < 0.0001) with the severity of airflow limitation and it correlated significantly (p < 0.0001) with airway resistance (r = 0.55) and specific conductance (r = −0.60) obtained from body-plethysmography. ζ also showed significant associations (p < 0.001) with diffusion capacity (r = −0.64), air-trapping (r = 0.68), and CT densitometry of emphysema (r = 0.40 against % below −950 HU and r = −0.34 against 15th percentile HU). Moreover, simulation studies demonstrated that an increase in ζ resulted in lower airflows from baseline. Therefore, we conclude that ζ quantifies airway resistance from forced expiration in spirometry—a method that is more abundantly available in primary care than traditional but expensive methods of measuring airway resistance such as body-plethysmography and forced oscillation technique. Full article
(This article belongs to the Special Issue Human Health Engineering)
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Open AccessArticle
Real-Time Model Predictive Control of Human Bodyweight Based on Energy Intake
Appl. Sci. 2019, 9(13), 2609; https://doi.org/10.3390/app9132609
Received: 3 June 2019 / Revised: 22 June 2019 / Accepted: 25 June 2019 / Published: 27 June 2019
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Abstract
The number of overweight people reached 1.9 billion in 2016. Lifespan decrease and many diseases have been linked to obesity. Efficient ways to monitor and control body weight are needed. The objective of this work is to explore the use of a model [...] Read more.
The number of overweight people reached 1.9 billion in 2016. Lifespan decrease and many diseases have been linked to obesity. Efficient ways to monitor and control body weight are needed. The objective of this work is to explore the use of a model predictive control approach to manage bodyweight in response to energy intake. The analysis is performed based on data obtained during the Minnesota starvation experiment, with weekly measurements on body weight and energy intake for 32 male participants over the course of 27 weeks. A first order dynamic auto-regression with exogenous variables model exhibits the best prediction, with an average mean relative prediction error value of 1.01 ± 0.02% for 1 week-ahead predictions. Then, the performance of a model predictive control algorithm, following a predefined bodyweight trajectory, is tested. Root mean square errors of 0.30 ± 0.06 kg and 9 ± 3 kcal day−1 are found between the desired target and simulated bodyweights, and between the measured energy intake and advised by the controller energy intake, respectively. The model predictive control approach for bodyweight allows calculating the needed energy intake in order to follow a predefined target bodyweight reference trajectory. This study shows a first possible step towards real-time active control of human bodyweight. Full article
(This article belongs to the Special Issue Human Health Engineering)
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Open AccessArticle
Discrete-Time Fractional Order Integral Sliding Mode Control of an Antagonistic Actuator Driven by Pneumatic Artificial Muscles
Appl. Sci. 2019, 9(12), 2503; https://doi.org/10.3390/app9122503
Received: 22 May 2019 / Revised: 17 June 2019 / Accepted: 18 June 2019 / Published: 19 June 2019
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Abstract
Recently, pneumatic artificial muscles (PAMs), a lightweight and high-compliant actuator, have been increasingly used in assistive rehabilitation robots. PAM-based applications must overcome two inherent drawbacks. The first is the nonlinearity due to the compressibility of the air, and the second is the hysteresis [...] Read more.
Recently, pneumatic artificial muscles (PAMs), a lightweight and high-compliant actuator, have been increasingly used in assistive rehabilitation robots. PAM-based applications must overcome two inherent drawbacks. The first is the nonlinearity due to the compressibility of the air, and the second is the hysteresis due to its geometric construction. Because of these drawbacks, it is difficult to construct not only an accurate mathematical model but also a high-performance control scheme. In this paper, the discrete-time fractional order integral sliding mode control approach is investigated to deal with the drawbacks of PAMs. First, a discrete-time second order plus dead time mathematical model is chosen to approximate the characteristics of PAMs in the antagonistic configuration. Then, the fractional order integral sliding mode control approach is employed together with a disturbance observer to improve the trajectory tracking performance. The effectiveness of the proposed control method is verified in multi-scenario experiments using a physical actuator. Full article
(This article belongs to the Special Issue Human Health Engineering)
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Open AccessArticle
Modeling of Motorized Orthosis Control
Appl. Sci. 2019, 9(12), 2453; https://doi.org/10.3390/app9122453
Received: 26 April 2019 / Revised: 11 June 2019 / Accepted: 13 June 2019 / Published: 15 June 2019
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Abstract
Orthotic devices are defined as externally applied devices that are used to modify the structural and functional characteristics of the neuro-muscular and skeletal systems. The aim of the current study is to improve the control and movement of a robotic arm orthosis by [...] Read more.
Orthotic devices are defined as externally applied devices that are used to modify the structural and functional characteristics of the neuro-muscular and skeletal systems. The aim of the current study is to improve the control and movement of a robotic arm orthosis by means of an intelligent optimization system. Firstly, the control problem settlement is defined with the muscle, brain, and arm model. Subsequently, the optimization control, which based on a differential evolution algorithm, is developed to calculate the optimum gain values. Additionally, a cost function is defined in order to control and minimize the effort that is made by the subject and to assure that the algorithm follows as close as possible the defined setpoint value. The results show that, with the optimization algorithm, the necessary development force of the muscles is close to zero and the neural excitation level of biceps and triceps signal values are getting lower with a gain increase. Furthermore, the necessary development force of the biceps muscle to overcome a load added to the orthosis control system is practically the half of the one that is necessary without the optimization algorithm. Full article
(This article belongs to the Special Issue Human Health Engineering)
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Open AccessArticle
Novel Design and Lateral Stability Tracking Control of a Four-Wheeled Rollator
Appl. Sci. 2019, 9(11), 2327; https://doi.org/10.3390/app9112327
Received: 25 April 2019 / Revised: 31 May 2019 / Accepted: 4 June 2019 / Published: 6 June 2019
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Abstract
Design and control of smart rollators have attracted increasing research interests in the past decades. To meet the requirements of the elderly or disabled users, this paper proposes a novel design and tracking control scheme for empowering and assisting natural human mobility with [...] Read more.
Design and control of smart rollators have attracted increasing research interests in the past decades. To meet the requirements of the elderly or disabled users, this paper proposes a novel design and tracking control scheme for empowering and assisting natural human mobility with a four-wheeled rollator. Firstly, by integrating the advantages of Kano Model Analysis and the Theory of Inventive Problem Solving (TRIZ), we introduce a novel Kano-TRIZ industrial design method to design and optimize its mechanical structure. The demand and quality characteristics of the clinical rollator are analyzed according to the Kano model. The Quality Function Deployment (QFD) and TRIZ are adopted to integrate industrial product innovations and optimize the function configuration. Furthermore, a lateral stability controller based on Model Predictive Control (MPC) scheme is introduced to achieve good tracking control performance with the lateral deviation and the heading angle deviation. Finally, the feasibility of the design and control method is verified with a simulation study. The simulation results indicate that the proposed algorithm keeps the lateral position error in a reasonable range. In the co-simulation of ADAMS-MATLAB, the trajectory of the rollator is smooth with constrained position error within 0.1 m, the turning angle and speed can achieve stable tracking control within 5 s and the heading angle is accurate and the speed is stable. A compared experiment with MPC and SMC show that MPC controller has faster response, higher tracking accuracy and smoother trajectory on the novel designed rollator. With the increasing demand for rollators in the global market, the methodology proposed in this paper will attract more research and industry interests. Full article
(This article belongs to the Special Issue Human Health Engineering)
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Open AccessArticle
Photoplethysmography-Based Continuous Systolic Blood Pressure Estimation Method for Low Processing Power Wearable Devices
Appl. Sci. 2019, 9(11), 2236; https://doi.org/10.3390/app9112236
Received: 13 April 2019 / Revised: 26 May 2019 / Accepted: 28 May 2019 / Published: 30 May 2019
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Abstract
Regardless of age, it is always important to detect deviations in long-term blood pressure from normal levels. Continuous monitoring of blood pressure throughout the day is even more important for elderly people with cardiovascular diseases or a high risk of stroke. The traditional [...] Read more.
Regardless of age, it is always important to detect deviations in long-term blood pressure from normal levels. Continuous monitoring of blood pressure throughout the day is even more important for elderly people with cardiovascular diseases or a high risk of stroke. The traditional cuff-based method for blood pressure measurements is not suitable for continuous real-time applications and is very uncomfortable. To address this problem, continuous blood pressure measurement methods based on photoplethysmogram (PPG) have been developed. However, these methods use specialized high-performance hardware and sensors, which are not available for common users. This paper proposes the continuous systolic blood pressure (SBP) estimation method based on PPG pulse wave steepness for low processing power wearable devices and evaluates its suitability using the commercially available CMS50FW Pulse Oximeter. The SBP estimation is done based on the PPG pulse wave steepness (rising edge angle) because it is highly correlated with systolic blood pressure. The SBP estimation based on this single feature allows us to significantly reduce the amount of data processed and avoid errors, due to PPG pulse wave amplitude changes resulting from physiological or external factors. The experimental evaluation shows that the proposed SBP estimation method allows the use of off-the-shelf wearable PPG measurement devices with a low sampling rate (up to 60 Hz) and low resolution (up to 8-bit) for precise SBP measurements (mean difference MD = −0.043 and standard deviation SD = 6.79). In contrast, the known methods for continuous SBP estimation are based on equipment with a much higher sampling rate and better resolution characteristics. Full article
(This article belongs to the Special Issue Human Health Engineering)
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Open AccessArticle
Long-Term Effects of a Soft Robotic Suit on Gait Characteristics in Healthy Elderly Persons
Appl. Sci. 2019, 9(9), 1957; https://doi.org/10.3390/app9091957
Received: 10 March 2019 / Revised: 30 April 2019 / Accepted: 8 May 2019 / Published: 13 May 2019
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Abstract
As a walking assistive device for elderly persons, one of the major aims should be to improve and rehabilitate gait characteristics after long-term repeated use of the device. However, most of the existing research on walking assistive devices only emphasize their immediate effects, [...] Read more.
As a walking assistive device for elderly persons, one of the major aims should be to improve and rehabilitate gait characteristics after long-term repeated use of the device. However, most of the existing research on walking assistive devices only emphasize their immediate effects, and there is limited research indicating the long-term effects. To address this gap, this paper experimentally validates the effects of our soft wearable robotic suit on gait characteristics of elderly persons after repeated use of the device for six weeks. Experimental results on four elderly subjects (age = 74.8 ± 5.0 year) show that, after six weeks of gait rehabilitation training by the robotic suit, the gait characteristics of the subjects were improved, leading to an increased walk ratio with an average of 9.8% compared with the initial state. The results of this research will benefit the potential use of the robotic suit in gait training and rehabilitation for elderly persons and also will be useful to the establishment of practical guidelines that maximize the training and rehabilitation effectiveness of the robotic suit. Full article
(This article belongs to the Special Issue Human Health Engineering)
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Open AccessFeature PaperArticle
Box-Jenkins Transfer Function Modelling for Reliable Determination of VO2 Kinetics in Patients with COPD
Appl. Sci. 2019, 9(9), 1822; https://doi.org/10.3390/app9091822
Received: 4 March 2019 / Revised: 11 April 2019 / Accepted: 29 April 2019 / Published: 1 May 2019
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Abstract
Oxygen uptake (VO2) kinetics provide information about the ability to respond to the increased physical load during a constant work rate test (CWRT). Box-Jenkins transfer function (BJ-TF) models can extract kinetic features from the phase II VO2 response during a [...] Read more.
Oxygen uptake (VO2) kinetics provide information about the ability to respond to the increased physical load during a constant work rate test (CWRT). Box-Jenkins transfer function (BJ-TF) models can extract kinetic features from the phase II VO2 response during a CWRT, without being affected by unwanted noise contributions (e.g., phase I contribution or measurement noise). CWRT data of 18 COPD patients were used to compare model fits and kinetic feature values between BJ-TF models and three typically applied exponential modelling methods. Autocorrelation tests and normalised root-mean-squared error values (BJ-TF: 2.8 ± 1.3%; exponential methods A, B and C: 10.5 ± 5.8%, 11.3 ± 5.2% and 12.1 ± 7.0%; p < 0.05) showed that BJ-TF models, in contrast to exponential models, could account for the most important noise contributions. This led to more reliable kinetic feature values compared to methods A and B (e.g., mean response time (MRT), BJ-TF: 74 ± 20 s; methods A-B: 100 ± 56 s–88 ± 52 s; p < 0.05). Only exponential modelling method C provided kinetic feature values comparable to BJ-TF features values (e.g., MRT: 75 ± 20 s). Based on theoretical considerations, we recommend using BJ-TF models, rather than exponential models, for reliable determinations of VO2 kinetics. Full article
(This article belongs to the Special Issue Human Health Engineering)
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Open AccessArticle
Determining Symptomatic Factors of Nomophobia in Peruvian Students from the National University of Engineering
Appl. Sci. 2019, 9(9), 1814; https://doi.org/10.3390/app9091814
Received: 1 February 2019 / Revised: 21 April 2019 / Accepted: 23 April 2019 / Published: 1 May 2019
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Abstract
The use of cell phones has increased worldwide in the past few decades, particularly in children and adolescents. Using these electronic devices provides personal benefits. Communicating through cell phones was a very important factor in the socioeconomic progress of developed countries. However, it [...] Read more.
The use of cell phones has increased worldwide in the past few decades, particularly in children and adolescents. Using these electronic devices provides personal benefits. Communicating through cell phones was a very important factor in the socioeconomic progress of developed countries. However, it is beyond doubt that its indiscriminate use can bring up certain psychiatric disorders or cause some disorder in a person, within the phobic group of anxiety disorders called nomophobia; basically associated with anxiety, nervousness, discomfort, and distress when contact with the smartphone is lost, mainly in the youngest users. This research proposal aims to identify symptoms that have not yet been detected by unceasing cell phone use, considering that in Peru there are few studies of human health engineering and the physical mental health. For that reason, we sought to identify the symptomatic factors of nomophobia presented by students at the National University of Engineering and its interference with their academic life. To accomplish this study, we designed a questionnaire according to our reality with the use of focus groups techniques when the test was taken in class. Three symptomatic factors of nomophobia were identified: feelings of anxiety, compulsive smartphone use, and feelings of anxiety and panic. The study included a representative sample of 461 students in different years of study engineering (21% women, 79% men, over 17 years of age). Finally, given the widespread adoption of smartphones and their integration into educational environments, the results of this study can help educators understand students’ inclination to use their smartphones at all times. Full article
(This article belongs to the Special Issue Human Health Engineering)
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Open AccessArticle
PANDAS: Paediatric Attention-Deficit/Hyperactivity Disorder Application Software
Appl. Sci. 2019, 9(8), 1645; https://doi.org/10.3390/app9081645
Received: 23 February 2019 / Revised: 27 March 2019 / Accepted: 28 March 2019 / Published: 20 April 2019
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Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a common neuropsychiatric disorder that impairs social, academic and occupational functioning in children, adolescents and adults. In South Africa, youth prevalence of ADHD is estimated as 10%. It is therefore necessary to further investigate methods that objectively diagnose, treat [...] Read more.
Attention-deficit/hyperactivity disorder (ADHD) is a common neuropsychiatric disorder that impairs social, academic and occupational functioning in children, adolescents and adults. In South Africa, youth prevalence of ADHD is estimated as 10%. It is therefore necessary to further investigate methods that objectively diagnose, treat and manage the disorder. The aim of the study was to develop a novel method that could be used as an aid to provide screening for ADHD. The study comprised of a beta-testing phase that included 30 children (19 non-ADHD and 11 ADHD) between the ages of 5 and 16 years old. The strategy was to use a tablet-based game that gathered real-time user data during game-play. This data was then used to train a linear binary support vector machine (SVM). The objective of the SVM was to differentiate between an ADHD individual versus a non-ADHD individual. A feature set was extracted from the gathered data and sequential forward selection (SFS) was performed to select the most significant features. The test set accuracy of 85.7% and leave-one-out cross-validation (LOOCV) accuracy of 83.5% were achieved. Overall, the classification accuracy of the trained SVM was 86.5%. Finally, the sensitivity of the model was 75% and this was seen as a moderate result. Since the sample size was fairly small, the results of the classifier were only seen as suggestive rather than conclusive. Therefore, the performance of the classifier was indicative that a quantitative tool could indeed be developed to perform screening for ADHD. Full article
(This article belongs to the Special Issue Human Health Engineering)
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Open AccessArticle
Older Adults’ Usability and Emotional Reactions toward Text, Diagram, Image, and Animation Interfaces for Displaying Health Information
Appl. Sci. 2019, 9(6), 1058; https://doi.org/10.3390/app9061058
Received: 1 February 2019 / Revised: 7 March 2019 / Accepted: 11 March 2019 / Published: 13 March 2019
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Abstract
Technology can facilitate the provision of healthcare to older adults. Wearable devices are thus increasingly prevalent amidst perpetual component miniaturization and cost reduction. This study aimed to determine whether existing application (app) interfaces are suitable for older adults by comparing the perceived usability [...] Read more.
Technology can facilitate the provision of healthcare to older adults. Wearable devices are thus increasingly prevalent amidst perpetual component miniaturization and cost reduction. This study aimed to determine whether existing application (app) interfaces are suitable for older adults by comparing the perceived usability and emotional reactions of younger users and older users to the health information display formats of wearable interfaces. Based on the outcomes of a literature review and expert recommendations, four health display interfaces—text, diagram, image, and animation—were developed and revised. Thirty respondents in Miaoli, Taiwan, were invited to participate in a questionnaire and interviews. The collected data were analyzed and discussed to develop design recommendations. The findings of this study were as follows: (1) the diagram interface had the lowest performance; (2) the respondents preferred the animation interface, which produced strong affective valence, thereby suggesting that animation generated positive emotions, yielding a result consistent with expert views and existing design principles; and (3) older users were more accepting of the text interface than the younger users, who exhibited negative emotions toward the text interface, highlighting a significant generation gap. Full article
(This article belongs to the Special Issue Human Health Engineering)
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Open AccessArticle
Effect of In-Shoe Foot Orthosis Contours on Heel Pain Due to Calcaneal Spurs
Appl. Sci. 2019, 9(3), 495; https://doi.org/10.3390/app9030495
Received: 27 November 2018 / Revised: 22 January 2019 / Accepted: 25 January 2019 / Published: 31 January 2019
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Abstract
The objective of this study is to investigate the effect of contouring the shoe insole on calcaneal pressure and heel pain in calcaneal spur patients. Calcaneal pressure was measured using three force sensors from 13 patients including three males and 10 females. These [...] Read more.
The objective of this study is to investigate the effect of contouring the shoe insole on calcaneal pressure and heel pain in calcaneal spur patients. Calcaneal pressure was measured using three force sensors from 13 patients including three males and 10 females. These patients have plantar heel pain due to calcaneal spurs, and we examined five customized contour insole foot areas (0–100%). Sensors were attached at the central heel (CH), lateral heel (LH) and medial heel (MH) of the foot. The pain was measured using an algometer and evaluated by the pain minimum compressive pressure (PMCP). In this study, it was observed that the calcaneal pressure decreased with increasing insole foot area. In addition, increasing the insole foot area from 25% to 50% can reduce the calcaneal pressure approximately 17.4% at the LH and 30.9% at the MH, which are smaller than the PMCP, while at the MH, pressure reduced 6.9%, which is greater than the PMCP. Therefore, to reduce pain, one can use 50% insole foot area, even though at MH it is still 19.3% greater than the PMCP. Excellent pain relief was observed when using 100% insole foot area, as the pressures in those three areas are lower than the PMCPs, but it is not recommended because it requires large production costs. Full article
(This article belongs to the Special Issue Human Health Engineering)
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Open AccessArticle
Effects of the Phantom Shape on the Gradient Artefact of Electroencephalography (EEG) Data in Simultaneous EEG–fMRI
Appl. Sci. 2018, 8(10), 1969; https://doi.org/10.3390/app8101969
Received: 11 September 2018 / Revised: 14 October 2018 / Accepted: 16 October 2018 / Published: 18 October 2018
Cited by 3 | PDF Full-text (17917 KB) | HTML Full-text | XML Full-text
Abstract
Electroencephalography (EEG) signals greatly suffer from gradient artefacts (GAs) due to the time-varying field gradients in the magnetic resonance (MR) scanner during the simultaneous acquisition of EEG and functional magnetic resonance imaging (fMRI) data. The GAs are the principal contributors of artefacts while [...] Read more.
Electroencephalography (EEG) signals greatly suffer from gradient artefacts (GAs) due to the time-varying field gradients in the magnetic resonance (MR) scanner during the simultaneous acquisition of EEG and functional magnetic resonance imaging (fMRI) data. The GAs are the principal contributors of artefacts while recording EEG inside an MR scanner, and most of them come from the interaction of the EEG cap and the subject’s head. Many researchers have been using a spherical phantom to characterize the GA in EEG data in combined EEG–fMRI studies. In this study, we investigated how the phantom shape could affect the characterization of the GA. EEG data were recorded with a spherical phantom, a head-shaped phantom, and six human subjects, individually, during the execution of customized and standard echo-planar imaging (EPI) sequences. The spatial potential maps of the root-mean-square (RMS) voltage of the GA over EEG channels for the trials with a head-shaped phantom closely mimicked those related to the human head rather than those obtained for the spherical phantom. This was confirmed by measuring the average similarity index (0.85/0.68). Moreover, a paired t-test showed that the head-shaped phantom’s and the spherical phantom’s data were significantly different (p < 0.005) from the subjects’ data, whereas the difference between the head-shaped phantom’s and the spherical phantom’s data was not significant (p = 0.07). The results of this study strongly suggest that a head-shaped phantom should be used for GA characterization studies in concurrent EEG–fMRI. Full article
(This article belongs to the Special Issue Human Health Engineering)
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