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Fulltext Telepointer technology in telemedicine: a review

Abdul Karim R, Zakaria NF, Zulkifley MA, Mustafa MM, Sagap I, Md Latar NH

Biomed Eng Online, 2013;12:21.
PMID: 23496940 DOI: 10.1186/1475-925X-12-21

Telepointer is a powerful tool in the telemedicine system that enhances the effectiveness of long-distance communication. Telepointer has been tested in telemedicine, and has potential to a big influence in improving quality of health care, especially in the rural area. A telepointer system works by sending additional information in the form of gesture that can convey more accurate instruction or information. It leads to more effective communication, precise diagnosis, and better decision by means of discussion and consultation between the expert and the junior clinicians. However, there is no review paper yet on the state of the art of the telepointer in telemedicine. This paper is intended to give the readers an overview of recent advancement of telepointer technology as a support tool in telemedicine. There are four most popular modes of telepointer system, namely cursor, hand, laser and sketching pointer. The result shows that telepointer technology has a huge potential for wider acceptance in real life applications, there are needs for more improvement in the real time positioning accuracy. More results from actual test (real patient) need to be reported. We believe that by addressing these two issues, telepointer technology will be embraced widely by researchers and practitioners.

Matched MeSH terms: Computers
Fulltext The usage of computers and internet web 2.0 in generation Y among university students (Penggunaan komputer dan internet Web 2.0 dalam kalangan generasi Y pelajar universiti)

Abdul Manaf, S.Z., Din, R., Hamdan, A., Mat Salleh, N.S., Kamsin, I.F., Abdul Aziz, J.

Journal of Advanced Research Design, 2015;7(1):10-18.
MyJurnal

At present, the learning activities carried out is in line with the rapid growth of development of technology and lifestyle. ICT literacy is categorised as those who can operate a computer and Internet. This study is conducted to determine the level of computer and Internet literacy in generation Y. A total of ten respondents among university students were interviewed. The level of the skill is measured in terms of the use of information processing systems and the Internet. The new knowledge addresses the themes in information communication technology literacy namely; defining, accessing, assessing, managing, integrating, creating and passing data. As such, the model of computer technology in education can also be produced. A more robust method of learning can be heightened by seeing the level of skills possessed by university students. The findings of this study is expected to determine the level of competence of the students and university can provide the necessary equipment to ensure effective teaching and learning.

Matched MeSH terms: Computers
Comparing the accuracy of density forecasts from competing GARCH models

Abu Hassan Shaari Mohd Nor, Ahmad Shamiri, Zaidi Isa

Sains Malaysiana, 2009;38.

In this research we introduce an analyzing procedure using the Kullback-Leibler information criteria (KLIC) as a statistical tool to evaluate and compare the predictive abilities of possibly misspecified density forecast models. The main advantage of this statistical tool is that we use the censored likelihood functions to compute the tail minimum of the KLIC, to compare the performance of a density forecast models in the tails. Use of KLIC is practically attractive as well as convenient, given its equivalent of the widely used LR test. We include an illustrative simulation to compare a set of distributions, including symmetric and asymmetric distribution, and a family of GARCH volatility models. Our results on simulated data show that the choice of the conditional distribution appears to be a more dominant factor in determining the adequacy and accuracy (quality) of density forecasts than the choice of volatility model.

Matched MeSH terms: Computers
Fulltext Word learning from a tablet app: Toddlers perform better in a passive context

Ackermann L, Lo CH, Mani N, Mayor J

PLoS One, 2020;15(12):e0240519.
PMID: 33259476 DOI: 10.1371/journal.pone.0240519

In recent years, the popularity of tablets has skyrocketed and there has been an explosive growth in apps designed for children. Howhever, many of these apps are released without tests for their effectiveness. This is worrying given that the factors influencing children's learning from touchscreen devices need to be examined in detail. In particular, it has been suggested that children learn less from passive video viewing relative to equivalent live interaction, which would have implications for learning from such digital tools. However, this so-called video deficit may be reduced by allowing children greater influence over their learning environment. Across two touchscreen-based experiments, we examined whether 2- to 4-year-olds benefit from actively choosing what to learn more about in a digital word learning task. We designed a tablet study in which "active" participants were allowed to choose which objects they were taught the label of, while yoked "passive" participants were presented with the objects chosen by their active peers. We then examined recognition of the learned associations across different tasks. In Experiment 1, children in the passive condition outperformed those in the active condition (n = 130). While Experiment 2 replicated these findings in a new group of Malay-speaking children (n = 32), there were no differences in children's learning or recognition of the novel word-object associations using a more implicit looking time measure. These results suggest that there may be performance costs associated with active tasks designed as in the current study, and at the very least, there may not always be systematic benefits associated with active learning in touchscreen-based word learning tasks. The current studies add to the evidence that educational apps need to be evaluated before release: While children might benefit from interactive apps under certain conditions, task design and requirements need to consider factors that may detract from successful performance.

Matched MeSH terms: Computers, Handheld
Towards reinforcing telemedicine adoption amongst clinicians in Nigeria

Adenuga KI, Iahad NA, Miskon S

Int J Med Inform, 2017 08;104:84-96.
PMID: 28599820 DOI: 10.1016/j.ijmedinf.2017.05.008

Telemedicine systems have been considered as a necessary measure to alleviate the shortfall in skilled medical specialists in developing countries. However, the obvious challenge is whether clinicians are willing to use this technological innovation, which has aided medical practice globally. One factor which has received little academic attention is the provision of suitable encouragement for clinicians to adopt telemedicine, in the form of rewards, motivation or incentives. A further consideration for telemedicine usage in developing countries, especially sub-Saharan Africa and Nigeria in particular, are to the severe shortage of available practising clinicians. The researchers therefore explore the need to positively reinforce the adoption of telemedicine amongst clinicians in Nigeria, and also offer a rationale for this using the UTAUT model. Data were collected using a structured paper-based questionnaire, with 252 physicians and nurses from six government hospitals in Ondo state, Nigeria. The study applied SmartPLS 2.0 for analysis to determine the relationship between six variables. Demographic moderating variables, age, gender and profession, were included. The results indicate that performance expectancy (p<0.05), effort expectancy (p<0.05), facilitating condition (p<0.01) and reinforcement factor (p<0.001) have significant effects on clinicians' behavioural intention to use telemedicine systems, as predicted using the extended UTAUT model. Our results showed that the use of telemedicine by clinicians in the Nigerian context is perceived as a dual responsibility which requires suitable reinforcement. In addition, performance expectancy, effort expectancy, facilitating condition and reinforcement determinants are influential factors in the use of telemedicine services for remote-patient clinical diagnosis and management by the Nigerian clinicians.

Matched MeSH terms: Attitude to Computers
Fulltext Observing Consistency in Online Communication Patterns for User Re-Identification

Adeyemi IR, Razak SA, Salleh M, Venter HS

PLoS One, 2016;11(12):e0166930.
PMID: 27918593 DOI: 10.1371/journal.pone.0166930

Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas.

Matched MeSH terms: Computers
Computerized segmentation and measurement of chronic wound images

Ahmad Fauzi MF, Khansa I, Catignani K, Gordillo G, Sen CK, Gurcan MN

Comput Biol Med, 2015 May;60:74-85.
PMID: 25756704 DOI: 10.1016/j.compbiomed.2015.02.015

An estimated 6.5 million patients in the United States are affected by chronic wounds, with more than US$25 billion and countless hours spent annually for all aspects of chronic wound care. There is a need for an intelligent software tool to analyze wound images, characterize wound tissue composition, measure wound size, and monitor changes in wound in between visits. Performed manually, this process is very time-consuming and subject to intra- and inter-reader variability. In this work, our objective is to develop methods to segment, measure and characterize clinically presented chronic wounds from photographic images. The first step of our method is to generate a Red-Yellow-Black-White (RYKW) probability map, which then guides the segmentation process using either optimal thresholding or region growing. The red, yellow and black probability maps are designed to handle the granulation, slough and eschar tissues, respectively; while the white probability map is to detect the white label card for measurement calibration purposes. The innovative aspects of this work include defining a four-dimensional probability map specific to wound characteristics, a computationally efficient method to segment wound images utilizing the probability map, and auto-calibration of wound measurements using the content of the image. These methods were applied to 80 wound images, captured in a clinical setting at the Ohio State University Comprehensive Wound Center, with the ground truth independently generated by the consensus of at least two clinicians. While the mean inter-reader agreement between the readers varied between 67.4% and 84.3%, the computer achieved an average accuracy of 75.1%.

Matched MeSH terms: Computers
Fulltext Bimodal Data Fusion of Simultaneous Measurements of EEG and fNIRS during Lower Limb Movements

Al-Quraishi MS, Elamvazuthi I, Tang TB, Al-Qurishi M, Adil SH, Ebrahim M

Brain Sci, 2021 May 27;11(6).
PMID: 34071982 DOI: 10.3390/brainsci11060713

Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have temporal and spatial characteristics that may complement each other and, therefore, pose an intriguing approach for brain-computer interaction (BCI). In this work, the relationship between the hemodynamic response and brain oscillation activity was investigated using the concurrent recording of fNIRS and EEG during ankle joint movements. Twenty subjects participated in this experiment. The EEG was recorded using 20 electrodes and hemodynamic responses were recorded using 32 optodes positioned over the motor cortex areas. The event-related desynchronization (ERD) feature was extracted from the EEG signal in the alpha band (8-11) Hz, and the concentration change of the oxy-hemoglobin (oxyHb) was evaluated from the hemodynamics response. During the motor execution of the ankle joint movements, a decrease in the alpha (8-11) Hz amplitude (desynchronization) was found to be correlated with an increase of the oxyHb (r = -0.64061, p < 0.00001) observed on the Cz electrode and the average of the fNIRS channels (ch28, ch25, ch32, ch35) close to the foot area representation. Then, the correlated channels in both modalities were used for ankle joint movement classification. The result demonstrates that the integrated modality based on the correlated channels provides a substantial enhancement in ankle joint classification accuracy of 93.01 ± 5.60% (p < 0.01) compared with single modality. These results highlight the potential of the bimodal fNIR-EEG approach for the development of future BCI for lower limb rehabilitation.

Matched MeSH terms: Computers
Fulltext Malay sentiment analysis based on combined classification approaches and Senti-lexicon algorithm

Al-Saffar A, Awang S, Tao H, Omar N, Al-Saiagh W, Al-Bared M

PLoS One, 2018;13(4):e0194852.
PMID: 29684036 DOI: 10.1371/journal.pone.0194852

Sentiment analysis techniques are increasingly exploited to categorize the opinion text to one or more predefined sentiment classes for the creation and automated maintenance of review-aggregation websites. In this paper, a Malay sentiment analysis classification model is proposed to improve classification performances based on the semantic orientation and machine learning approaches. First, a total of 2,478 Malay sentiment-lexicon phrases and words are assigned with a synonym and stored with the help of more than one Malay native speaker, and the polarity is manually allotted with a score. In addition, the supervised machine learning approaches and lexicon knowledge method are combined for Malay sentiment classification with evaluating thirteen features. Finally, three individual classifiers and a combined classifier are used to evaluate the classification accuracy. In experimental results, a wide-range of comparative experiments is conducted on a Malay Reviews Corpus (MRC), and it demonstrates that the feature extraction improves the performance of Malay sentiment analysis based on the combined classification. However, the results depend on three factors, the features, the number of features and the classification approach.

Matched MeSH terms: Attitude to Computers
Fulltext A systematic review of automated pre-processing, feature extraction and classification of cardiotocography

Al-Yousif S, Jaenul A, Al-Dayyeni W, Alamoodi A, Jabori I, Md Tahir N, et al.

PeerJ Comput Sci, 2021;7:e452.
PMID: 33987454 DOI: 10.7717/peerj-cs.452

Context: The interpretations of cardiotocography (CTG) tracings are indeed vital to monitor fetal well-being both during pregnancy and childbirth. Currently, many studies are focusing on feature extraction and CTG classification using computer vision approach in determining the most accurate diagnosis as well as monitoring the fetal well-being during pregnancy. Additionally, a fetal monitoring system would be able to perform detection and precise quantification of fetal heart rate patterns.
Objective: This study aimed to perform a systematic review to describe the achievements made by the researchers, summarizing findings that have been found by previous researchers in feature extraction and CTG classification, to determine criteria and evaluation methods to the taxonomies of the proposed literature in the CTG field and to distinguish aspects from relevant research in the field of CTG.
Methods: Article search was done systematically using three databases: IEEE Xplore digital library, Science Direct, and Web of Science over a period of 5 years. The literature in the medical sciences and engineering was included in the search selection to provide a broader understanding for researchers.
Results: After screening 372 articles, and based on our protocol of exclusion and inclusion criteria, for the final set of articles, 50 articles were obtained. The research literature taxonomy was divided into four stages. The first stage discussed the proposed method which presented steps and algorithms in the pre-processing stage, feature extraction and classification as well as their use in CTG (20/50 papers). The second stage included the development of a system specifically on automatic feature extraction and CTG classification (7/50 papers). The third stage consisted of reviews and survey articles on automatic feature extraction and CTG classification (3/50 papers). The last stage discussed evaluation and comparative studies to determine the best method for extracting and classifying features with comparisons based on a set of criteria (20/50 articles).
Discussion: This study focused more on literature compared to techniques or methods. Also, this study conducts research and identification of various types of datasets used in surveys from publicly available, private, and commercial datasets. To analyze the results, researchers evaluated independent datasets using different techniques.
Conclusions: This systematic review contributes to understand and have insight into the relevant research in the field of CTG by surveying and classifying pertinent research efforts. This review will help to address the current research opportunities, problems and challenges, motivations, recommendations related to feature extraction and CTG classification, as well as the measurement of various performance and various data sets used by other researchers.

Matched MeSH terms: Computers
Fulltext Critical Factors Influencing Decision to Adopt Human Resource Information System (HRIS) in Hospitals

Alam MG, Masum AK, Beh LS, Hong CS

PLoS One, 2016;11(8):e0160366.
PMID: 27494334 DOI: 10.1371/journal.pone.0160366

The aim of this research is to explore factors influencing the management decisions to adopt human resource information system (HRIS) in the hospital industry of Bangladesh-an emerging developing country. To understand this issue, this paper integrates two prominent adoption theories-Human-Organization-Technology fit (HOT-fit) model and Technology-Organization-Environment (TOE) framework. Thirteen factors under four dimensions were investigated to explore their influence on HRIS adoption decisions in hospitals. Employing non-probability sampling method, a total of 550 copies of structured questionnaires were distributed among HR executives of 92 private hospitals in Bangladesh. Among the respondents, usable questionnaires were 383 that suggesting a valid response rate of 69.63%. We classify the sample into 3 core groups based on the HRIS initial implementation, namely adopters, prospectors, and laggards. The obtained results specify 5 most critical factors i.e. IT infrastructure, top management support, IT capabilities of staff, perceived cost, and competitive pressure. Moreover, the most significant dimension is technological dimension followed by organisational, human, and environmental among the proposed 4 dimensions. Lastly, the study found existence of significant differences in all factors across different adopting groups. The study results also expose constructive proposals to researchers, hospitals, and the government to enhance the likelihood of adopting HRIS. The present study has important implications in understanding HRIS implementation in developing countries.

Matched MeSH terms: Attitude to Computers
Fulltext The Modern and Digital Transformation of Oral Health Care: A Mini Review

Alauddin MS, Baharuddin AS, Mohd Ghazali MI

Healthcare (Basel), 2021 Jan 25;9(2).
PMID: 33503807 DOI: 10.3390/healthcare9020118

Dentistry is a part of the field of medicine which is advocated in this digital revolution. The increasing trend in dentistry digitalization has led to the advancement in computer-derived data processing and manufacturing. This progress has been exponentially supported by the Internet of medical things (IoMT), big data and analytical algorithm, internet and communication technologies (ICT) including digital social media, augmented and virtual reality (AR and VR), and artificial intelligence (AI). The interplay between these sophisticated digital aspects has dramatically changed the healthcare and biomedical sectors, especially for dentistry. This myriad of applications of technologies will not only be able to streamline oral health care, facilitate workflow, increase oral health at a fraction of the current conventional cost, relieve dentist and dental auxiliary staff from routine and laborious tasks, but also ignite participatory in personalized oral health care. This narrative article review highlights recent dentistry digitalization encompassing technological advancement, limitations, challenges, and conceptual theoretical modern approaches in oral health prevention and care, particularly in ensuring the quality, efficiency, and strategic dental care in the modern era of dentistry.

Matched MeSH terms: Computers
Fulltext Technique for Early Reliability Prediction of Software Components Using Behaviour Models

Ali A, N A Jawawi D, Adham Isa M, Imran Babar M

PLoS One, 2016 Sep 26;11(9):e0163346.
PMID: 27668748 DOI: 10.1371/journal.pone.0163346

Behaviour models are the most commonly used input for predicting the reliability of a software system at the early design stage. A component behaviour model reveals the structure and behaviour of the component during the execution of system-level functionalities. There are various challenges related to component reliability prediction at the early design stage based on behaviour models. For example, most of the current reliability techniques do not provide fine-grained sequential behaviour models of individual components and fail to consider the loop entry and exit points in the reliability computation. Moreover, some of the current techniques do not tackle the problem of operational data unavailability and the lack of analysis results that can be valuable for software architects at the early design stage. This paper proposes a reliability prediction technique that, pragmatically, synthesizes system behaviour in the form of a state machine, given a set of scenarios and corresponding constraints as input. The state machine is utilized as a base for generating the component-relevant operational data. The state machine is also used as a source for identifying the nodes and edges of a component probabilistic dependency graph (CPDG). Based on the CPDG, a stack-based algorithm is used to compute the reliability. The proposed technique is evaluated by a comparison with existing techniques and the application of sensitivity analysis to a robotic wheelchair system as a case study. The results indicate that the proposed technique is more relevant at the early design stage compared to existing works, and can provide a more realistic and meaningful prediction.

Matched MeSH terms: Computers
Changes in human milk vitamin E and total lipids during the first twelve days of lactation

Ali J, Kader HA, Hassan K, Arshat H

Am J Clin Nutr, 1986 Jun;43(6):925-30.
PMID: 3717068

Our previous study showed vitamin E deficiency in newborns (69.7%) and mothers at term (85.9%) when the ratio between serum vitamin E in mg/dl and total lipids in g/dl was used as an indicator of vitamin E status. This study was conducted to determine the human milk content of vitamin E. During the first 12 days of lactation milk vitamin E levels remained almost constant (day 1, 0.68 mg/dl; day 12, 0.65 mg/dl), milk total lipid levels increased daily (day 1, 1.11 g/dl; day 12, 3.60 g/dl), and the ratio between milk vitamin E and total lipids dropped steadily (day 1, 1.3; day 12, 0.2). In spite of this drop in vitamin E status, it is unlikely that vitamin E availability will be affected in neonates, because normal neonates absorb milk fats well and this ability increases with age.

Matched MeSH terms: Computers
Fulltext Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge

Ali S, Ghatwary N, Jha D, Isik-Polat E, Polat G, Yang C, et al.

Sci Rep, 2024 Jan 23;14(1):2032.
PMID: 38263232 DOI: 10.1038/s41598-024-52063-x

Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, appearance, and location makes the detection of polyps challenging. Moreover, colonoscopy surveillance and removal of polyps are highly operator-dependent procedures and occur in a highly complex organ topology. There exists a high missed detection rate and incomplete removal of colonic polyps. To assist in clinical procedures and reduce missed rates, automated methods for detecting and segmenting polyps using machine learning have been achieved in past years. However, the major drawback in most of these methods is their ability to generalise to out-of-sample unseen datasets from different centres, populations, modalities, and acquisition systems. To test this hypothesis rigorously, we, together with expert gastroenterologists, curated a multi-centre and multi-population dataset acquired from six different colonoscopy systems and challenged the computational expert teams to develop robust automated detection and segmentation methods in a crowd-sourcing Endoscopic computer vision challenge. This work put forward rigorous generalisability tests and assesses the usability of devised deep learning methods in dynamic and actual clinical colonoscopy procedures. We analyse the results of four top performing teams for the detection task and five top performing teams for the segmentation task. Our analyses demonstrate that the top-ranking teams concentrated mainly on accuracy over the real-time performance required for clinical applicability. We further dissect the devised methods and provide an experiment-based hypothesis that reveals the need for improved generalisability to tackle diversity present in multi-centre datasets and routine clinical procedures.

Matched MeSH terms: Computers
Fulltext Fruit Battery Method for Oil Palm Fruit Ripeness Sensor and Comparison with Computer Vision Method

Aliteh NA, Minakata K, Tashiro K, Wakiwaka H, Kobayashi K, Nagata H, et al.

Sensors (Basel), 2020 Jan 23;20(3).
PMID: 31979252 DOI: 10.3390/s20030637

Oil palm ripeness' main evaluation procedure is traditionally accomplished by human vision. However, the dependency on human evaluators to grade the ripeness of oil palm fresh fruit bunches (FFBs) by traditional means could lead to inaccuracy that can cause a reduction in oil palm fruit oil extraction rate (OER). This paper emphasizes the fruit battery method to distinguish oil palm fruit FFB ripeness stages by determining the value of load resistance voltage and its moisture content resolution. In addition, computer vision using a color feature is tested on the same samples to compare the accuracy score using support vector machine (SVM). The accuracy score results of the fruit battery, computer vision, and a combination of both methods' accuracy scores are evaluated and compared. When the ripe and unripe samples were tested for load resistance voltage ranging from 10 Ω to 10 kΩ, three resistance values were shortlisted and tested for moisture content resolution evaluation. A 1 kΩ load resistance showed the best moisture content resolution, and the results were used for accuracy score evaluation comparison with computer vision. From the results obtained, the accuracy scores for the combination method are the highest, followed by the fruit battery and computer vision methods.

Matched MeSH terms: Computers
Pixel-based skin colour detection techniques evaluation

Alnned M. Mharib, Mohammad Hamiruce Marhaban, Abdul Rahman Ramli

Pertanika Journal of Science & Technology, 2007;15(2):131-137.
MyJurnal

Skin detection has gained popularity and importance in the computer vision community. It is an essential step for important vision tasks such as the detection, tracking and recognition of face, segmentation of hand for gesture analysis, person identification, as well as video surveillance and filtering of objectionable web images. All these applications are based on the assumption that the regions of the human skin are already located. In the recent past, numerous techniques for skin colour modeling and recognition have been proposed. The aims of this paper are to compile the published pixel-based skin colour detection techniques to describe their key concepts and try to find out and summarize their advantages, disadvantages and characteristic features.

Matched MeSH terms: Computers
Fulltext Survey of computer literacy among patients with schizophrenia: potential of developing a computerised cognitive remediation program in Kota Bharu, Malaysia.

Alwi, M.N.M., Roslaili, R., Noraniza Hayati, M.N., Harris, A.W.F.

Malaysian Journal of Psychiatry, 2006;14(1):23-28.
MyJurnal

The aim of the study was to acquire background information on computer literacy among schizophrenia patients in Kota Bharu, Malaysia, prior to the introduction of a computerised cognitive remediation programme in the local setting.
Method: Fifty consenting consecutive patients with schizophrenia attending the Universiti Sains Malaysia Hospital psychiatric clinic were surveyed using the Computer Literacy Scale (CLS), a scale designed to specifically look at their level of computer knowledge, confidence and attitude towards computers.
Results: The majority of the patients studied have had schizophrenia for 5 years or less. While the majority of them have used computers befoie, about half had a poor level of knowledge, although they showed reasonable confidence and a positive attitude towards computers. Few played computer games.
Conclusions: Implementation of a computerised cognitive remediation programme in the Malaysian setting has a promising potential based on the results of this study but the programme needs to be adapted in light of the negative attitudes towards the use of games.
Study site: Psychiatric clinc, Hospital Universiti Sains Malaysia (HUSM), Kelantan, Malaysia

Matched MeSH terms: Computers
Fulltext Objective triceps muscle strength measurement using computerized adaptation

Amalourde A, Vinayaga P, Naveed N, Choon SK, Zaleha O

Med J Malaysia, 2004 Dec;59 Suppl F:8-13.
PMID: 15941154

In our centre the non-availability computerized exercise machines limits the objective monitoring of strength rehabilitation. We undertook this research programme to objectively measure triceps muscle strength by interfacing NORSK-Gym machine with accelerometer and positional transducers to a computer. This data was tabulated and processed using Microsoft Excel. The positional transducer was first calibrated and it showed an excellent Pearson Correlation Coefficients against a standard metric reading (r = 0.9999). Peak Force was used as a test parameter for isotonic triceps muscle strength measurements. The criterion-referenced validity was established as the peak forces measured using the accelerometer and positional transducer demonstrated identical Peak Forces (r = 0.94). Analysis of our mean Peak Force measurements using non-biological force as well as the intra-individual reproducibility demonstrated excellent Pearson Correlation Coefficients (r) = 0.982-0.998 and 0.929-0.972 respectively. This computerized adaptation of the NORSK-Gym machine produced an objective, valid and reproducible triceps muscle strength measurement.

Matched MeSH terms: Computers*
Position of document holder and work related risk factors for neck pain among computer users: a narrative review

Ambusam S, Baharudin O, Roslizawati N, Leonard J

Clin Ter, 2015 Nov-Dec;166(6):256-61.
PMID: 26794814 DOI: 10.7417/CT.2015.1898

Document holder is used as a remedy to address occupational neck pain among computer users. An understanding on the effects of the document holder along with other work related risk factors while working in computer workstation requires attention. A comprehensive knowledge on the optimal location of the document holder in computer use and associated work related factors that may contribute to neck pain reviewed in this article. A literature search has been conducted over the past 14 years based on the published articles from January 1990 to January 2014 in both Science Direct and PubMed databases. Medical Subject Headings (MeSH) keywords for search were neck muscle OR head posture OR muscle tension' OR muscle activity OR work related disorders OR neck pain AND/OR document location OR document holder OR source document OR copy screen holder.Document holder placed lateral to the screen was most preferred to reduce neck discomfort among occupational typists. Document without a holder was placed flat on the surface is least preferred. The head posture and muscle activity increases when the document is placed flat on the surface compared to when placed on the document holder. Work related factors such as static posture, repetitive movement, prolong sitting and awkward positions were the risk factors for chronic neck pain. This review highlights the optimal location for document holder for computer users to reduce neck pain. Together, the importance of work related risk factors for to neck pain on occupational typist is emphasized for the clinical management.

Matched MeSH terms: Computers

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