MyMedR

Displaying all 10 publications

Abstract:

Sort:

Fulltext The elderly in Malaysia: demographic trends

Karim HA

Med J Malaysia, 1997 Sep;52(3):206-12.
PMID: 10968086

The process of development in Malaysia has brought about significant socioeconomic and demographic transformations. Reduction in fertility and mortality, have resulted in increasing survival of populations to later life. Thus the proportion of the elderly is increasing. Population ageing, the most salient change affecting the demographic profile of Malaysia, will have a significant impact on the patterns of socio-economic development. In order to anticipate and respond in time to the far reaching socio-economic and humanitarian implications of ageing, it is imperative that the magnitude and the
momentum of its occurrence need to be recognised.
This paper looks at demographic trends, disease profile as well as health policy implications of ageing in Malaysia.
Research to prevent injuries

Krishnan R, Karim H

World Health Forum, 1998;19(2):159-60.
PMID: 9652215
Study of rigevidon for oral contraception in a family planning clinic in Kota Bahru, Kelantan

Ang Eng Suan, Karim HA

Malays J Reprod Health, 1990 Jun;8(1):31-7.
PMID: 12316342
Breast-feeding and the urban poor in developing countries

Serva V, Karim H, Ebrahim GJ

J Trop Pediatr, 1986 06;32(3):127-9.
PMID: 3747002 DOI: 10.1093/tropej/32.3.127
Characteristics and prosthesis usage of amputees attending Medical Rehabilitation services in Malaysia

Karim HHA, Chern PM

Med J Malaysia, 2020 09;75(5):519-524.
PMID: 32918420

INTRODUCTION: Increasing numbers of limb amputation are performed globally and in Malaysia due to the rise of complications because of Diabetes Mellitus (DM). Limb amputation influences many aspects of an individual's life, and prosthesis restoration is one of the primary rehabilitation goals to help amputees resume daily activities. As limited information is available in Malaysia, this study aims to determine the socio-demographic, clinical characteristics and prosthesis usage among the amputees.
METHODS: A cross-sectional study using self-developed survey form was conducted at 13 Medical Rehabilitation Clinics in Malaysia among 541 upper and lower limb amputees of any duration and cause.
RESULTS: The study population had a mean age of 54 years. Majority were males, Malays, married and had completed secondary school. About 70% of amputations were performed due to DM complications and at transtibial level. Fifty-eight percent of unilateral lower limb amputees were using prosthesis with a mean (standard deviation) of 6.48 (±4.55) hours per day. Time since amputation was the true factor associated with prosthesis usage. Longer hours of prosthesis use per day was positively correlated with longer interval after prosthesis restoration (r=0.467).
CONCLUSION: Higher aetiology of DM and lower prosthesis usage among amputees may be because of high prevalence of DM in Malaysia. The prosthesis usage and hours of use per day were low compared to the international reports, which may be influenced by sampling location and time since amputation. Nevertheless, this is a novel multicentre study on the characteristics and prosthesis usage of amputees. Hopefully, this research will assist to support, facilitate and promote prosthesis rehabilitation in Malaysia.
Fulltext Fusion of Appearance and Motion Features for Daily Activity Recognition from Egocentric Perspective

Lye MH, AlDahoul N, Abdul Karim H

Sensors (Basel), 2023 Jul 30;23(15).
PMID: 37571588 DOI: 10.3390/s23156804

Vidos from a first-person or egocentric perspective offer a promising tool for recognizing various activities related to daily living. In the egocentric perspective, the video is obtained from a wearable camera, and this enables the capture of the person's activities in a consistent viewpoint. Recognition of activity using a wearable sensor is challenging due to various reasons, such as motion blur and large variations. The existing methods are based on extracting handcrafted features from video frames to represent the contents. These features are domain-dependent, where features that are suitable for a specific dataset may not be suitable for others. In this paper, we propose a novel solution to recognize daily living activities from a pre-segmented video clip. The pre-trained convolutional neural network (CNN) model VGG16 is used to extract visual features from sampled video frames and then aggregated by the proposed pooling scheme. The proposed solution combines appearance and motion features extracted from video frames and optical flow images, respectively. The methods of mean and max spatial pooling (MMSP) and max mean temporal pyramid (TPMM) pooling are proposed to compose the final video descriptor. The feature is applied to a linear support vector machine (SVM) to recognize the type of activities observed in the video clip. The evaluation of the proposed solution was performed on three public benchmark datasets. We performed studies to show the advantage of aggregating appearance and motion features for daily activity recognition. The results show that the proposed solution is promising for recognizing activities of daily living. Compared to several methods on three public datasets, the proposed MMSP-TPMM method produces higher classification performance in terms of accuracy (90.38% with LENA dataset, 75.37% with ADL dataset, 96.08% with FPPA dataset) and average per-class precision (AP) (58.42% with ADL dataset and 96.11% with FPPA dataset).
A study of the acceptability and effectiveness of Norplant (R) contraceptive implants in Kuala Lumpur, Malaysia

Arshat H, Rachagan SP, Kwa Siew Kim, Ang Eng Suan, Karim HA, Ismail MT

Malays J Reprod Health, 1990 Jun;8(1):21-9.
PMID: 12316341
A Randomized Clinical Trial Testing a Parenting Intervention Among Afghan and Rohingya Refugees in Malaysia

Shaw SA, Ward KP, Pillai V, Ali LM, Karim H

Fam Process, 2021 09;60(3):788-805.
PMID: 32981083 DOI: 10.1111/famp.12592

Refugee families experience uncertainty and stress when residing in countries of first asylum, such as Malaysia, and may benefit from supportive parenting interventions. In the greater Kuala Lumpur, Malaysia area we piloted an eight-week parenting program with 79 Rohingya and Afghan mothers in nine separate groups. Participants were randomized to an intervention group or a waitlist control group and those in each arm completed a 3-month follow-up assessment. Program content addressed positive discipline, strengthening family relationships, adapting to a new environment, and improving health and emotional well-being. Measures assessed included child intensity and parenting self-efficacy from the Child Adjustment and Parent Efficacy Scale; positive parenting, inconsistent discipline, and poor supervision from the Alabama Parenting Questionnaire-Short Form; family intimacy and family conflict from the Family Functioning Scale, and emotional well-being from the Refugee Health Screening-15. Participating in the intervention led to beneficial changes in child intensity, parenting self-efficacy, family intimacy, family conflict, and emotional distress for the treatment group, and all changes except for emotional distress were maintained over time. However, the intervention did not lead to changes in positive parenting, inconsistent discipline, or poor supervision in the treatment group. Findings point to the potential benefits of parenting programs for refugee communities in transitory settings and contribute to the limited body of literature examining such programs.
Fulltext Translation, Cross-Cultural Adaptation to Malay, and psychometric evaluation of the AIM-IAM-FIM questionnaire: Measuring the implementation outcome of a community-based intervention programme

Salleh H, Avoi R, Abdul Karim H, Osman S, Kaur N, Dhanaraj P

PLoS One, 2023;18(11):e0294238.
PMID: 37972041 DOI: 10.1371/journal.pone.0294238

BACKGROUND: The implementation outcomes determine the success and progress of a community-based intervention programme. The community is an important stakeholder whose effects should be assessed. Nevertheless, Malaysia has limited instruments for determining outcome measurements. This research aimed to develop Malay versions of the Acceptability, Appropriateness, and Feasibility Intervention Measures (AIM-IAM-FIM) questionnaire, which evaluates the implementation outcome of the programme.
METHODS: A methodological study of the translation and validation of the implementation outcome measures was conducted from March 2022 until December 2022. Three key analyses were conducted: (1) translation and validation; (2) factor investigation and extraction (n = 170); and (3) scale evaluation (n = 235).
RESULT: The Malay version measuring the implementation outcome measures of a community-based intervention programme was produced after extensive translation and modification, and it consisted of a single dimension with seven items. The content validity index was 0.9, the exploratory factor analysis showed that the KMO measure of sample adequacy was 0.9277, and Bartlett's sphericity test was statistically significant. Cronbach's alpha was good, with a level of 0.938. The single factor structure fitted the data satisfactorily [χ2 (p-value of 0.002), SRMR = 0.030, CFI = 0.999, RMSEA = 0.079, TLI = 0.998]. Factor loading for all items was > 0.7.
CONCLUSION: The 7-item Malay version of the AIM-IAM-FIM survey instrument is valid and reliable for assessing the acceptability of a community-based intervention study and is applicable to other fields. Future studies in psychometric evaluation are recommended in other states due to the variety of Malay dialects spoken across Asia. The scale may also benefit other areas where the language is spoken.
Fulltext Cortical signals analysis to recognize intralimb mobility using modified RNN and various EEG quantities

Al-Quraishi MS, Tan WH, Elamvazuthi I, Ooi CP, Saad NM, Al-Hiyali MI, et al.

Heliyon, 2024 May 15;10(9):e30406.
PMID: 38726180 DOI: 10.1016/j.heliyon.2024.e30406

Electroencephalogram (EEG) signals are critical in interpreting sensorimotor activities for predicting body movements. However, their efficacy in identifying intralimb movements, such as the dorsiflexion and plantar flexion of the foot, remains suboptimal. This study aims to explore whether various EEG signal quantities can effectively recognize intralimb movements to facilitate the development of Brain-Computer Interface (BCI) devices for foot rehabilitation. This research involved twenty-two healthy, right-handed participants. EEG data were collected using 21 electrodes positioned over the motor cortex, while two electromyography (EMG) electrodes recorded the onset of ankle joint movements. The study focused on analyzing slow cortical potential (SCP) and sensorimotor rhythms (SMR) in alpha and beta bands from the EEG. Five key features-fourth-order Autoregressive feature, variance, waveform length, standard deviation, and permutation entropy-were extracted. A modified Recurrent Neural Network (RNN) including Long Short-term Memory (LSTM) and Gated Recurrent Unit (GRU) algorithms was developed for movement recognition. These were compared against conventional machine learning algorithms, including nonlinear Support Vector Machine (SVM) and k Nearest Neighbourhood (kNN) classifiers. The performance of the proposed models was assessed using two data schemes: within-subject and across-subjects. The findings demonstrated that the GRU and LSTM models significantly outperformed traditional machine learning algorithms in recognizing different EEG signal quantities for intralimb movement. The study indicates that deep learning models, particularly GRU and LSTM, hold superior potential over standard machine learning techniques in identifying intralimb movements using EEG signals. Where the accuracies of LSTM for within and across subjects were 98.87 ± 1.80 % and 87.38 ± 0.86 % respectively. Whereas the accuracy of GRU within and across subjects were 99.18 ± 1.28 % and 86.44 ± 0.69 % respectively. This advancement could significantly benefit the development of BCI devices aimed at foot rehabilitation, suggesting a new avenue for enhancing physical therapy outcomes.