Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control

Instrumented wheelchair operates based on surface electromyography (sEMG) is one of alternative to assist impairment person for mobility. SEMG is chosen due to good in accuracy and easier preparation to place the electrodes. Motor neuron transmit electrical potential to muscle fibre to perform isometric, concentric or eccentric contraction. These electrical changes that is called Motor Unit Action Potential (MUAP) can be acquired and amplified by electrodes located on targeted muscles changes can be recorded and analysed using sEMG devices. But, sEMG device cost up to USD 2,100 for a sEMG data acquisition device that available on market is one of the drawback to be used by impairment person that most of them has financial problem due to unable to work like before. In addition, it is a closed source system that cannot be modified to improve the accuracy and adding more features. Open source system such as Arduino has limitation of specifications that makes able to apply nonpattern recognition control methods which is simpler and easier compared to pattern recognition. However, classification accuracy is lower than pattern recognition and it cannot be applied to higher number participants from different background and gender. This research aims are to develop an open-source Arduino based sEMG data acquisition device by formulating hybrid automata algorithm to differentiate MUAP activity during wheelchair propulsion. Addition of hybrid automata algorithm to run pattern and non-pattern recognition based control methods is an advantage to increase accuracy in differentiating forward stroke or hand return activity. Electrodes are placed on Biceps (BIC), Triceps (TRI), Extensor (EXT), Flexor (FIX) and MUAP activity recorded for 30 healthy persons. Then, experiment result was validated with simulation result using OpenSim biomedical modelling software. Mean, standard deviation (SD), confidence interval (CI) and maximum point different (MPD) of MUAP were calculated and to be used as thresholds for non-pattern recognition control method in method selection experiment. Meanwhile, pattern recognition is using Probability Density Function (PDF) to determine MUAP according to type of activities. Total of ten control methods determined from population and individual data were tested against another 10 healthy persons to evaluate the algorithm performance. Assessment of each control method done by misclassification matrix looking at True Positive (TP) and False Negative (FN) of power assist system activation period. Developed sEMG data acquisition device that is operated by Arduino MEGA 2560 and Myoware muscle sensors with sampling rate of above 400Hz successfully recorded MUAP from four arm muscles. Furthermore, 2.5 ms of average data latency for device to record, analyse, validate and creating commands to activate the power assist system. Data obtained from the device shows that most active muscle during wheelchair propulsion is TRI, followed by BIC and matched to OpenSim simulation result. In method selection experiment, 96.28% of average accuracy was achieved and different control methods were selected by misclassification matrix for each of persons. This method would be a control method to activate power assist system and selected based on conditions set in the algorithm. These findings indicated that open source Arduino board is capable of running real time pattern, non-pattern recognition based control methods by producing classification accuracy up to 99.48% even though it is known as just a microcontroller that has limitation to run complex classifiers. At the same time, a device that cost less than USD200 has 400Hz of sampling rate is as good as closed source device that is come with expensive price tag to own it. Based on algorithm evaluation, it shows that one control method couldn’t fit to all persons as per proven in method selection experiment. Different person has different control method that suit them the most. Lastly, BIC and TRI can be reference muscles to activate assistive device in instrumented wheelchair that is using propulsion as indication

Morphometric analysis as an application tool to differentiate three local pen shells species

Pen shells are generally large bivalves, triangular in shape with light yellow-brown to dark brown colour. They live with their pointed end embedded in sediment, attached by abundant fine byssal threads. Pen shells are relatively common at the sandy substrate of the seagrass beds inhabited by Enhalus acoroides, Halophila spp. and Cymodocea serulata, shallow lagoons and coral rubble areas. Specimens of Pinna bicolor Gmelin, Pinna deltodes Menke and Pinna atropurpurea Sowerby were collected from the seagrass beds of Merambong Shoal, Tanjung Adang Shoal and Merambong Island off South Western coast, of Johor, Peninsular Malaysia for morphological studies from August 2005 to June 2006. Naturally, P. deltodes is largely found on hard bottom substrate while, P. bicolor and P. atropurpurea are more associated with soft substrate. Physically, there was no significant external morphological difference between P. bicolor, P. deltodes and P. atropurpurea. The species was identified on the basis of nine internal and external characteristics of the valves. The three species were found to be morphologically different (P<0.05) on the basis of four major characteristics viz width of sulcus (WS), distance between posterior adductor muscle to posterior dorsal nacreous layer (PAMPDNL), dorsal posterior margin length (DPML) and shell width length (WL)

Biodiversity and distribution of pen shells (Bivalvia: Pinnidae) from the seagrass beds of Sungai Pulai, Peninsular Malaysia

Studies on biodiversity and distribution of pen shells were conducted at Merambong Shoal (N1 19’ 55.62” E103 35’ 57.75”), Tanjung Adang Shoal (N1 19’ 48.03” E103 33’ 59.44”) oo oo and Merambong Island (N1 18’ 54.83” E103 36’ 33.37”) off South Western Johor coast, Malaysia oo from August 2005 to June 2006. A total of 135 individuals were collected from three different stations. Pinna bicolor and Pinna atropurpurea were dominance. Higher density of pen shells were recorded in St 1 with 0.027 ind/m and St 2 was recorded lower density with 0.004 ind/m at 22 Merambong Shoal. Univariate analysis at Merambong Shoal population recorded higher values for diversity and richness indices compared to Tanjung Adang Shoal and Merambong Island but the value of Evenness index was quite similar between the three stations. Fifty eight individuals of pen shell were collected from study areas for taxonomy identification. Seven groups of pen shell were identified base on the internal and external surface of the valves of pen shell. Seven species were clearly identified which Pinna and Atrina were dominant from the seagrass bed of Sungai Pulai, Peninsular Malaysia

Development of Jogja Tourism App using GPS-Based Tracking Augmented Reality

The number of tourists every year continues to increase, but the pandemic resulted in tourists experiencing a decrease, and activity also prioritized social distancing. With the reduction of tourists and human interaction, media are needed to help tourists still visit Jogja by minimizing interaction. The method used to build applications in Research and Development. The first stage is the need analysis and literature study. The second stage is a design that uses use-case diagram. The third stage is implementing or developing applications and quality assurance testing. The fourth stage is the stage of testing software for users and knowing the feasibility of the application. The results showed that the results of the application work were excellent, with a percentage of 85.11%, which means the application is suitable for the Jogja Tourism App

Age, growth and length-weight relationships of Pinna bicolor Gmelin (Bivalvia: Pinnidae) in the Seagrass Beds of Sungai Pulai Estuary, Johor, Peninsular Malaysia.

Age and growth of Pinna bicolor were examined in the seagrass beds of Merambong shoal (N 1°19′55.62″; E 103°35′57.75″) off the south-western coast of Johor, Peninsular Malaysia between May 2006 and April 2007. Monthly growth increment data of P. bicolor were analyzed using FiSAT software (FAO-ICLARM Stock Assessment Tools) to estimate the asymptotic length (L∞) and growth coefficient (K). Average growth rate of P. bicolor was 1.42 (±0.01) cm per month; the estimated asymptotic length (L∞) and growth coefficient (K) were 34.66 cm and 0.88 per year, respectively. In their natural habitat, P. bicolor attain shell heights of approximately 17, 25 and 30 cm at the end of their first, second and third years of growth. The length–weight relationship was estimated as Log W = −5.397 + 3.111Log L, and in exponential form the equation was W = 0.000004L3.111 (r2 = 0.99, P < 0.01). Habitat temperature and salinity ranged between 27.47 and 29.66°C and 28.66–33.00 ppt with a mean of 29.10 (±0.66) m°C and 30.52 (±1.41) ppt, respectively

New distribution record of two pen shells (Bivalvia : Pinnidae) from the Seagrass Beds of Sg. Pulai, Johore Malaysia

Studies on taxonomy of pen shells were conducted at Merambong Shoal (N1° 19’ 55.62? E103° 35’ 57.75? ), Tanjung Adang Shoal (N1° 19’ 48.03? E103° 33’ 59.44? ) and Merambong Island (N1° 18’ 54.83? E103° 36’ 33.37? ) off South Western Johor coast, Peninsular Malaysia from August 2005 to June 2006. One hundred and seven individuals of pen shells were collected from the study areas for taxonomy identification. Pen shells were grouped based on the internal and external surface of the valves. Seven species were clearly identified where Atrina and Pinna are dominant. Among these seven species, "Pinna deltodes (Menke, 1843) and Pinna incurva (Gmelin, 1791)" are the new distribution record from the seagrasses bed of Sungai Pulai

Sexual polymorphism in a population of Strombus canarium Linnaeus, 1758 (Mollusca: Gastropoda) at Merambong Shoal Malaysia

Sexual polymorphism in a population of Strombus canarium Linnaeus, 1758 (Mollusca: Gastropoda) at Merambong Shoal, Malaysia. Zoological Studies 47 (3): 318-325. Various morphometric parameters of Strombus canarium Linnaeus, 1758 from Merambong Shoal, Malaysia, were measured and analyzed. The parameters include shell length, body whorl length, shell width, shell depth, shell lip thickness, aperture length, animal weight and shell weight. The population showed sexual polymorphism, and in addition to normal males and females, a 3rd morph composed of abnormal females with imposex characters were present. The latter(imposex females) accounted for 35.71% of the total adult female sub-population. Comparisons between males and normal females showed that the former had a significantly larger, heavier, and more-elongate shell than the latter. The male shells also had a significantly thicker lip with a higher degree of posterior and lateral lip flaring. Conversely, females allocated more energy into tissue production than shell deposition relative to males. The 3rd imposex morph had a significantly larger and heavier shell, and a higher degree of thickening and flaring of the lip compared with both male and normal female shells. Imposex females also allocated less energy to gonad production relative to tissue production compared to normal females

Morphological characteristics of pinna bicolor gmelin and pinna deltodes menke from the seagrass bed of Sungai Pulai, Johor, Peninsular Malaysia

Samples of Pinna bicolor Gmelin and Pinna deltodes Menke were collected from the seagrass bed of Sungai Pulai, covering Merambong shoal, Tanjung Adang shoal and Merambong Island off south western coast of Johor, Malaysia for morphological study from August 2005 to June 2006. It was observed that P. deltodes is associated with hard substratum and P. bicolor is associated with soft substratum in the study area. Physically there was no difference between P. bicolor and P. deltodes. The species were identified on the basis of nine internal and external characteristics of the valves. The two species were found to be morphologically different on the basis of width of sulcus, distance between posterior adductor muscle to posterior dorsal nacreous layer, dorsal posterior margin length and shell width

Evaluation of misclassification matrix method in validation of an assistive device for manual wheelchair propulsion

Classification accuracy is essential in the bio signal’s performance-based assistive devices. In this study, surface electromyography (SEMG) signals acquisition was extracted from 3 healthy right-handed participants. SEMG signal was processed, and Motor Unit Action Potential (MUAP) was determined. Accuracy, precision, sensitivity and specificity were calculated in real-time based on individual MUAP, critically compared with pattern and non-pattern recognition control methods by Misclassification Matrix inserted into Arduino MEGA 2560 Microcontroller. The results indicated that the performance of each control method is different for every participant and a comparison tool is a must to select the best out of it. It shows that the misclassification matrix filtered the best control method for participant 1 as Probability Density Function, no for participant 2 and Maximum Point Different (MPD) for participant 3 based on determined conditions

Intelligent Machining Systems for Robotic End-Effectors: State-of-the-Art and Toward Future Directions

This review paper delves into the advancements brought about by Industry 4.0 in the realm of intelligent machining systems for robotic end-effectors. Robotic end-effectors, which are the devices at the end of a robotic arm, have seen significant enhancements in their design, development, and application across various sectors, from manufacturing to healthcare. The integration of intelligent machining systems into these end-effectors has augmented their efficiency, precision, and flexibility. The paper also highlights the role of intelligent control systems in boosting the performance of these robotic systems. Despite the progress, challenges persist, such as improving machining accuracy, optimizing machining trajectories, and integrating machine learning techniques. The review concludes by identifying gaps in the current research and suggests potential areas for future exploration to further enhance the capabilities of robotic end-effectors