Kinect-based physiotherapy and assessment: a comprehensive review

In this paper, we discuss a review of the present Kinect-based physiotherapy and assessment for rehabilitation patients to provide an outline of the state of art, limitation and issues of concern as well as suggestion for future work in this approach. The paper is constructed into three main parts, each part presenting a review for a particular topic. The introduction was discussed on physiotherapy exercises and the limitation of current Kinect-based applications. Next, we also discuss on Kinect Skeleton Joint and Kinect Depth Map features that being used widely nowadays. A concise summary with significant findings of each paper had been tabulate for each feature; Skeleton Joints and Depth Map. Afterward we assemble a quite number of classification method that being implemented for activity recognition in past few years

Case study for Pelorus Intelligence and Technology Academy Sdn. Bhd. : SWOT analysis for Netherlands Maritime Institute of Technology (NMIT) / Nur Syafiqah Nor Rashid

SWOT analysis is a tool for auditing in an organization and its environment. SWOT analysis is the first stage of planning and helps marketers to focus on key issues before any decision can be made. This case study analyses the strength, weakness, opportunity and threat or known as SWOT Analyses on Netherlands Maritime Institute of Technology (NMIT) for PELORUS Intelligence and Technology Academy Sdn. Bhd. This case study first will identify as many as possible factor for each element’s, then the researcher will select the major factor for each element’s and conduct research to support each factor

Plant-Based Milk As An Alternative To Dairy Milk - The Challenges And Way Forward

This literature review aims to discuss the technological constraint faced during the processing of plant-based milk and to review the nutritional properties, sensory acceptability, stability, functional and application challenges of plant-based milk. Plant-based milk can be defined as a liquid that has a particle size distribution of 5-10μm resulted from the breakdown of plant material and homogenization process. Plant-based milk can be made from cereal, legume, seed, nut and pseudo-cereal. The examples of plant-based milk are oats milk, soymilk, almond milk, rice milk, coconut milk, peanut milk and sesame milk. While dairy milk has already well accepted by consumer, plant-based milk still faces challenges to grow in the market. Plant-based milk has problem related to elimination of anti-nutrient factors and limitations of heat treatment applied in the processing. The conventional heating is unable to eliminate all the undesirable compounds. The nutritional properties of plant-based milk are not comparable to dairy milk without fortification and quality of protein of plant-based is lower than dairy milk in terms of amino acids array. The issue of sensory properties for plant-based milk is basically caused by beany flavour due to the presence of some undesirable compounds such as lipoxygenase, hexanal and isoflavones. Besides, plant-based milk normally made up of big particles such as protein and carbohydrate that leads to phase separation on storage. This can be solved by the addition of gums but the right type and amount of gums should be carefully decided to prevent unnecessary interaction with compounds naturally present in the product

Human resource practices in a non governmental organization: A case study at Malaysian Nature Society (MNS)

Malaysian Nature Society (MNS) is one of the largest and longest surviving NGOs in Malaysia. MNS is dependent upon membership fees through subscriptions as a main source of income; however it is not adequate to cover the cost of running MNS. The biggest challenge in MNS is to seek financial support through projects to maintain and sustain the organization. This exploratory qualitative research was carried out to study the human resource management practices in an Non-Governmental Organization (NGO) in a Malaysian context. Issues and challenges were also examined. Applying saturation and purposive sampling in this study, ten respondents were interviewed. Data gathered were transcribed, sorted, coded and analysed manually using Excel. Findings in this study revealed three themes, namely leadership, career development, and compensation and benefits. This study proposed with effective leadership, career development, and compensation and benefits, employees will perform better, increase retention and reduce high staff turnover. Majority of the participants also mentioned about the low salaries. Salary is the biggest motivator and MNS should look into a salary revision periodicall

Development of spike train algorithms for physiotherapy assessment using deep learning approaches

Physiotherapy nowadays has become a demanding medication for curing bones related injuries and pain to restore someone's to health in order to gain back the ability to cope with daily living tasks. As the technologies of sensors have risen, smart physiotherapy monitoring systems become trendy researches due to its potential to enhance the quality of physiotherapy assessment. However, varied sensor technologies of physiotherapy assessment have lacked versatility and robustness. This research proposed a spike train feature extraction for physiotherapy assessment to enhance the patient's progression. However, the concerns are how capable is spike trains in achieving high accuracy as other related works on recognising and assessing rehabilitation movements. In this context, spike trains are defined as sequences of recorded times when neurons fire spikes or also known as action potentials. This study implemented a spike train as a primary method of feature extraction that illustrated a significant pattern for each exercise performed.Three datasets, UI-PRMD dataset, K3Da dataset, and Self-Collected dataset have been adopted in the studies to be encoded into spike trains formal representation which resulting to an average of 415 spike patterns. Next, the patterns of raster plots were being trained as the input into a deep learning framework to evaluate the accuracy of the pattern's uniqueness. Furthermore, this study makes use of the occurrence of spikes' number, which is known as firing rate, to distinguish movements' correctness and being compared with the deep learning evaluation measures to prove the efficiency of deep learning prediction. The proposed framework achieved recognition rates of 99.44%, 98.21%, and 100.00% for UI-PRMD, K3Da, and self-collected datasets, respectively. These results proved that the proposed framework achieved targetable accuracy for all datasets trained with various CNN architectures. Next, the experimental results of physiotherapy assessment indicate that the correctness prediction by the proposed framework closely follows the ground-truth value for the movements. This study is among the first successful attempts of implementing spike train into a deep learning framework for a real-time-based rehabilitation session case study with promising results. Hence, spike train is the foremost choice as features that are hugely rewarding towards deep learning as it can visually differentiate each of the physiotherapy movements with unique patterns

Microbiological and Chemical Quality of Keropok Lekor during Processing And Storage

Keropok lekor is an important fish product in Malaysia. The customers’ demands for keropok lekor have been increasing. This study was conducted to analyze the microbiological and chemical quality of keropok lekor in every stage of its processing, namely mincing, mixing, kneading, boiling and cooling. Subsequently, this study was also undertaken in an attempt to determine the effectiveness of post processing treatment on keropok lekor in order to prolong its shelf life. The method used to analyze the microbiological quality is known as the direct plate counts for the total plate counts (TPC), psychrotrophic, yeasts and molds, mesophilic sporeformer, Staphylococcus aureus, total coliform and fecal coliform counts. Simple biochemical test was carried out to identify the presumptive bacteria present in keropok lekor processing. Chemical quality was analyzed on the total volatile bases (TVB) and trimethylamine (TMA), using Conway microdiffusion method, and biogenic amines was done using the High Performance Liquid Chromatography (HPLC). The post-processing treatments on keropok lekor were exposing keropok lekor to UV light for 15 or 30 min, either coated with different concentrations of ascorbic acid (500, 1000 or 1500 ppm) or dipped in hot oil for 3, 6 or 9 s, and stored at the room temperature for 7 d or at chill temperature (4±1°C) for 14 d. When processing keropok lekor, the boiling of keropok lekor at 100°C for 10 min reduced the TPC (4.38±0.47 log10 cfu/g), psychrotrophic counts (2.00 ± 0.00 log10 cfu/g), mesophilic sporeformer counts (1.26 ± 0.34 log10 cfu/g) and total coliform counts (1.71±0.51 log MPN/g) significantly (p>0.05). However, the microbial counts were found to increase significantly (p<0.05) after the cooling process, except for the yeast and mold counts and S. aureus counts. The presumptive predominant microorganisms, isolated before the boiling stage, were members of the Enterobacteriaceae family and those belonging to Pseudomonas, Vibrio, Staphylococcus, Bacillus and Micrococcus genus. After the boiling stage, the presumptive predominant microorganisms were members of Enterobacteriace family and those belonging to Micrococcus, Bacillus, Staphylococcus and Aerococcus genus. As for the chemical quality, TVB and TMA levels were indicated to significantly decrease (p<0/05) after boiling from 7.29 to 4.68 mg/ 100g and 3.38 to 1.81 mg/ 100g, respectively, but not for the putrescine, cadaverine and histamine levels. Before the boiling stage, presumptive microorganisms producing putrescine, cadaverine and histamine were members of the Enterobacteriaceae family, as well as members of Staphylococcus, Pseudomonas and Micrococcus genus. Members of the genus Pseudomonas, which produce biogenic amines, were not isolated from keropok lekor after the boiling stage. The post-processing treatment which was applied on keropok lekor was found to enhance both its quality and shelf life. The results showed that exposing keropok lekor to UV light for 15 min and dipping it in hot oil for 9 s had extended the shelf life of this snack for 5 d when v stored at the room temperature, and for 14 d when stored at 4±1°C. This post processing treatment had also caused a significant reduction in TPC, psychrotrophic count, yeasts and molds count, TVB, as well as TMA and putrescine, cadaverine and histamine level. On the contrary, ascorbic acid was not as effective in increasing the shelf life of keropok lekor or in reducing TVB, TMA and putrescine, cadaverine and histamine level, as compared to dipping it in hot oil

Development of optical test strip for rapid determination of trace arsenic using immobilized gallocyanine

Irreversible test strip for the determination of arsenic has been developed. It has a rectangular sensing zone containing all the reagents necessary to produce a selective response to arsenic and formed by immobilized gallocyanine inside chitosan membrane. This method offer sensitivity and simplicity in detecting arsenic as no prior treatment or extraction is required. A linear response was attained in the arsenic concentration in the range of 10 to 30 ppm with calculated limit of detection of 0.96 ppm. This method also showed a reproducible result with relative standard deviation (RSD) of 0.87% and response time of ~5min. Interference studies showed that Pb(II) and Ni(II) significantly interfered during the determination. The developed sensor has been validated against Atomic Absorption Spectroscopy method and proven comparable

"Litter marks" around oil palm tree base indicating infiltration area of stemflow-induced water

The “litter marks” which has the dark color and shape like a circle was found around the oil palm tree base. These litter marks seem to be caused by the infiltration excess overland flow due to higher intensity of stemflow than the infiltration capacity of surface soil. An experiment was conducted to determine relationships between the diameter at the tree base and the radius of litter mark or infiltration area mark from the center of the stem. Result shows that the litter marks around oil palm tree base can be a useful indicator to estimate the infiltration area of stemflow-induced water

Semantic object detection for human activity monitoring system

Semantic object detection is significant for activity monitoring system. Any abnormalities occurred in a monitored area can be detected by applying semantic object detection that determines any displaced objects in the monitored area. Many approaches are being made nowadays towards better semantic object detection methods, but the approaches are either resource consuming such as using sensors that are costly or restricted to certain scenarios and background only. We assume that the scale structures and velocity can be estimated to define a different state of activity. This project proposes Histogram of Oriented Gradient (HOG) technique to extract feature points of semantic objects in the monitored area while Histogram of Oriented Optical Flow (HOOF) technique is used to annotate the current state of the semantic object that having human-and-object interaction. Both passive and active objects are extracted using HOG, and HOOF descriptor indicate the time series status of the spatial and orientation of the semantic object. Support Vector Machine technique uses the predictors to train and test the input video and classify the processed dataset to its respective activity class. We evaluate our approach to recognise human actions in several scenarios and achieve 89% accuracy with 11.3% error rate

Optimal accelerometer placement for fall detection of rehabilitation patients

The development of health monitoring system using wearable sensor has lots of potential in the field of rehabilitation and gained lots of attention in the scientific community and industry. The aim and motivation in this field are to focus on the application of wearable technology to monitor elderly or rehab patients in home-based settings to reduce resources and development cost. The wearable sensor such as accelerometer used to emphasise the clinical applications of fall detection during rehabilitation treatment. This paper is intended to determine the optimal sensor placement especially for lower limb activity during rehabilitation exercise. Accelerometer data were collected from three different body locations (hip, thigh, and foot). The lower limb activities involve normal movements such as walking, lifting, sit-to-stand, and stairs. Other unexpected activity such as falls might occur during normal lower limb exercise movement. Then, acceleration data for various lower limbs activities was classified using k-NN and SVM classifier. The result found that the hip was the best location to record data for lower limb activities including when fall occurs