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Static pinch strength against a therapist's gentle pull is evaluated using the pincer grasp component of the Fugl Meyer Assessment (FMA) to assess pinch impairment after stroke. In the pincer grasp component, therapists applied a gentle pull to distinguish between a score of 1 (moderate pinch impairment) and a score of 2 (no pinch impairment). The gentle pull is described as a resistance equivalent to a manual muscle test (MMT) score 4/5. The accepted use of "gentle" as a qualitative description for the pull results is a non-standardized subjective interpretation. The goal of this paper was to determine the quantitative value of the gentle pull applied by the therapists as in their clinical practice using a pinch-pull gripping system. The FMA protocol was used to standardize the body and fingers positions of three occupational therapists who were then instructed to apply a gentle pull of 4/5 MMT using their thumb and index fingers (in a tip-to-tip pinch). The results show that the therapists exerted a mean gentle pull (4/5 MMT score) of 6.34 ± 0.98 N with high reliability and acceptable repeatability. In investigating the ability of healthy subjects to resist the gentle pull, 50 adult male volunteers were instructed to pinch the pincer object and resist a dynamic loading exerted by the pinch-pull gripping system as much as possible to the moment the pincer object slips away. The results show that all subjects were able to exert a pulling force higher than the quantitative value of the gentle pull.

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The coronavirus COVID-19 has recently started to spread rapidly in Malaysia. The number of total infected cases has increased to 3662 on 05 April 2020, leading to the country being placed under lockdown. As the main public concern is whether the current situation will continue for the next few months, this study aims to predict the epidemic peak using the Susceptible-Exposed-Infectious-Recovered (SEIR) model, with incorporation of the mortality cases. The infection rate was estimated using the Genetic Algorithm (GA), while the Adaptive Neuro-Fuzzy Inference System (ANFIS) model was used to provide short-time forecasting of the number of infected cases. The results show that the estimated infection rate is 0.228 ± 0.013, while the basic reproductive number is 2.28 ± 0.13. The epidemic peak of COVID-19 in Malaysia could be reached on 26 July 2020, with an uncertain period of 30 days (12 July-11 August). Possible interventions by the government to reduce the infection rate by 25% over two or three months would delay the epidemic peak by 30 and 46 days, respectively. The forecasting results using the ANFIS model show a low Normalized Root Mean Square Error (NRMSE) of 0.041; a low Mean Absolute Percentage Error (MAPE) of 2.45%; and a high coefficient of determination (R2) of 0.9964. The results also show that an intervention has a great effect on delaying the epidemic peak and a longer intervention period would reduce the epidemic size at the peak. The study provides important information for public health providers and the government to control the COVID-19 epidemic.

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Tissue recovery is important in preventing tissue deterioration, which is induced by pressure and may lead to pressure ulcers (PU). Reactive hyperaemia (RH) is an indicator used to identify people at risk of PU. In this study, the effect of different recovery times on RH trend is investigated during repetitive loading. Twenty-one male Sprague-Dawley rats (seven per group), with body weight of 385-485 g, were categorised into three groups and subjected to different recovery times with three repetitive loading cycles. The first, second, and third groups were subjected to short (3 min), moderate (10 min), and prolonged (40 min) recovery, respectively, while fixed loading time and pressure (10 min and 50 mmHg, respectively). Peak hyperaemia was measured in the three cycles to determine trends associated with different recovery times. Three RH trends (increasing, decreasing, and inconsistent) were observed. As the recovery time is increased (3 min vs. 10 min vs. 40 min), the number of samples with increasing RH trend decreases (57% vs. 29% vs. 14%) and the number of samples with inconsistent RH trend increases (29% vs. 57% vs. 72%). All groups consists of one sample with decreasing RH trend (14%). Results confirm that different recovery times affect the RH trend during repetitive loading. The RH trend may be used to determine the sufficient recovery time of an individual to avoid PU development.

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Anaesthesia is a multivariable problem where a combination of drugs are used to induce desired hypnotic, analgesia and immobility states. The automation of anaesthesia may improve the safety and cost-effectiveness of anaesthesia. However, the realization of a safe and reliable multivariable closed-loop control of anaesthesia is yet to be achieved due to a manifold of challenges. In this paper, several significant challenges in automation of anaesthesia are discussed, namely model uncertainty, controlled variables, closed-loop application and dependability. The increasingly reliable measurement device, robust and adaptive controller, and better fault tolerance strategy are paving the way for automation of anaesthesia.

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Early detection of knee osteoarthritis (OA) is of great interest to orthopaedic surgeons, rheumatologists, radiologists, and researchers because it would allow physicians to provide patients with treatments and advice to slow the onset or progression of the disease. Early detection can be achieved by identifying early changes in selected features of degenerative articular cartilage (AC) using non-invasive imaging modalities. Magnetic resonance imaging (MRI) is becoming the standard for assessment of OA. The aim of this paper was to review the influence of MRI on the selection, detection, and measurement of AC features associated with early OA. Our review of the literature indicates that the changes associated with early OA are in cartilage thickness, cartilage volume, cartilage water content, and proteoglycan content that can be accurately, consistently, and non-invasively measured using MRI. Choosing an MR pulse sequence that provides the capability to assess cartilage physiology and morphology in a single acquisition and advanced multi-nuclei MRI is desirable. The results of the review indicate that using an ultra-high magnetic strength, MR imager does not affect early OA detection. In conclusion, MRI is currently the most suitable modality for early detection of knee OA, and future research should focus on the quantitative evaluation of early OA features using advances in MR hardware, software, and data processing with sophisticated image/pattern recognition techniques.

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