Multiple Linear Regression in Predicting Motor Assessment Scale of Stroke Patients

The Multiple Linear Regression (MLR) is a predictive model that was commonly used to predict the clinical score of stroke patients. However, the performance of the predictive model slightly depends on the method of feature selection on the data as input predictor to the model. Therefore, appropriate feature selection method needs to be investigated in order to give an optimum performance of the prediction. This paper aims (i) to develop predictive model for Motor Assessment Scale (MAS) prediction of stroke patients, (ii) to establish relationship between kinematic variables and MAS score using a predictive model, (iii) to evaluate the prediction performance of a predictive model based on root mean squared error (RMSE) and coefficient of determination R2. Three types of feature selection methods involve in this study which are the combination of all kinematic variables, the combination of the best four or less kinematic variables, and the combination of kinematic variables based on p < 0.05. The prediction performance of MLR model between two assessment devices (iRest and ReHAD) has been compared. As the result, MLR model for ReHAD with the combination of kinematic variables that has p < 0.05 as input predictor has the best performance with Draw I (RMSEte = 1.9228, R2 = 0.8623), Draw Diamond (RMSEte = 2.6136, R2 = 0.7477), and Draw Circle (RMSEte = 2.1756, R2 = 0.8268). These finding suggest that the relationship between kinematic variables and MAS score of stoke patients is strong, and the MLR model with feature selection of kinematic variables that has p < 0.05 is able to predict the MAS score of stroke patients using the kinematic variables extracted from the assessment device

Rehabilitation system for paraplegic patients using mind machine interface; a conceptual framework

Mind-Machine Interface (MMI) is a newly surfaced term in the field of control engineering and rehabilitation systems. This technique, coupled with the existing functional electrical stimulation (FES) systems, can be very beneficial for effective rehabilitation of disabled patients. This paper presents a conceptual framework for the development of MMI based FES systems for therapeutic aid and function restoration in spinal cord injured (SCI) paraplegic patients. It is intended to acquire thought modulated signals from human brain and then use these signals to command and control FES as desired by the patient. The proposed setup can significantly assist the rehabilitation and recovery of paraplegic patients due to the ease of control for the user

Force Control for One Degree of Freedom Haptic Device using PID Controller

Haptics has been used as an additional feedback to increase human experience to the environment over years and its application has been widening into education, manufacturing and medical. The most developed haptic devices are for rehabilitation purpose. The rehabilitation process usually depends on the physiotherapist. But, it requires repetitive movements for long-term rehabilitation, thus haptic devices are needed. Most of the rehabilitation devices are included with haptic feedback to enhance therapy exercise during the rehabilitation process. However, the devices come with multiple degrees of freedom (DOF), complex design and costly. Rehabilitation for hand movement such as grasping, squeezing, holding and pinching usually does not need an expensive and complex device. Therefore, the goal of this study is to make an enhancement to One DOF Haptic Device for grasping rehabilitation exercise. It is improved to perform a force control mechanism with few types of conventional controller which are Proportional (P) controller, Proportional-Integral (PI) controller, Proportional-Derivative (PD) controller and Proportional-Integral-Derivative (PID) controller. The performance of the haptic device is tested with different conventional controller to obtain the best proposed controller based on the lowest value of Mean Square Error (MSE). The results show that PID Controller (MSE = 0.0028) is the most suitable for the haptic device with Proportional gain (Kp), Integral gain (Ki) and Derivative gain (Kd) are 1.3, 0.01 and 0.2 respectively. The force control mechanism can imitate the training motion of grasping movement for the patient

Uptake of Hydrocarbon by Pseudomonas fluorescens (P1) and Pseudomonas putida (K1) Strains in the Presence of Surfactants: A Cell Surface Modification

The objective of this research was the evaluation of the effects of exogenous added surfactants on hydrocarbon biodegradation and on cell surface properties. Crude oil hydrocarbons are often difficult to remove from the environment because of their insolubility in water. The addition of surfactants enhances the removal of hydrocarbons by raising the solubility of these compounds. These surfactants cause them to become more vulnerable to degradation, thereby facilitating transportation across the cell membrane. The obtained results showed that the microorganism consortia of bacteria are useful biological agents within environmental bioremediation. The most effective amongst all, as regards biodegradation, were the consortia of Pseudomonas spp. and Bacillus spp. strains. The results indicated that the natural surfactants (rhamnolipides and saponins) are more effective surfactants in hydrocarbon biodegradation as compared to Triton X-100. The addition of natural surfactants enhanced the removal of hydrocarbon and diesel oil from the environment. Very promising was the use of saponins as a surfactant in hydrocarbon biodegradation. This surfactant significantly increases the organic compound biodegradation. In the case of those surfactants that could be easily adsorbed on cells of strains (e.g., rhamnolipides), a change of hydrophobicity to ca. 30–40% was noted. As the final result, an increase in hydrocarbon biodegradation was observed

Yeasts and bacterial biosurfactants as demulsifiers for petroleum derivative in seawater emulsions

Abstract Oil sludge or waste generated in transport, storage or refining forms highly stable mixtures due to the presence and additives with surfactant properties and water forming complex emulsions. Thus, demulsification is necessary to separate this residual oil from the aqueous phase for oil processing and water treatment/disposal. Most used chemical demulsifiers, although effective, are environmental contaminants and do not meet the desired levels of biodegradation. We investigated the application of microbial biosurfactants as potential natural demulsifiers of petroleum derivatives in water emulsions. Biosurfactants crude extracts, produced by yeasts (Candida guilliermondii, Candida lipolytica and Candida sphaerica) and bacteria (Pseudomonas aeruginosa, Pseudomonas cepacia and Bacillus sp.) grown in industrial residues, were tested for demulsification capacity in their crude and pure forms. The best results obtained were for bacterial biosurfactants, which were able to recover about 65% of the seawater emulsified with motor oil compared to 35–40% only for yeasts products. Biosurfactants were also tested with oil-in-water (O/W) and water-in-oil (W/O) kerosene model emulsions. No relationship between interfacial tension, cell hydrophobicity and demulsification ratios was observed with all the biosurfactants tested. Microscopic illustrations of the emulsions in the presence of the biosurfactants showed the aspects of the emulsion and demulsification process. The results obtained demonstrate the potential of these agents as demulsifiers in marine environments