Moving approximate entropy and its application to the electromyographic control of an artificial hand

A multiple-degree-of-freedom artificial hand has been developed at the University of Southampton with the aim of including control philosophies to form a highly functional prosthesis hand. Using electromyographic signals is an established technique for the control of a hand. In it simplest form, the signals allow for opening a hand and subsequent closing to grasp an object.This thesis describes the work carried out in the development of an electromyographic control system, with the aim to have a simple and robust method. A model of the control system was developed to differentiate grip postures using two surface electromyographic signals. A new method, moving approximate entropy was employed to investigate whether any significant patterns can be observed in the structure of the electromyographic signals. An investigation, using moving approximate entropy, on twenty healthy participants' wrist muscles (flexor carpi ulnaris and extensor carpi radialis) during wrist exion, wrist extension and cocontraction at different speeds has shown repeatable and distinct patterns at three states of contraction: start, middle and end. An analysis of the results also showed differences at different speeds of contraction. There is a low variation of the approximate entropy values between participants. This result, if used in the control of an artificial hand, would eliminate any training requirement. Other methods, mean absolute value, number of zero crossings, sample entropy, standard deviation, skewness and kurtosis have been determined from the signals. Of these features, mean absolute value and kurtosis were selected for information extraction. These three methods: moving approximate entropy, mean absolute value and kurtosis are used in the feature extraction process of the control system. A fuzzy logic system is used to classify the extracted information in discriminating the final grip posture. The results demonstrate the ability of the system to classify the information related to different grip postures

Success factors of rebranding strategy of Telekom Malaysia from the employee perspectives / Siti Anom Ahmad

The major functions of Telekom Malaysia (TM) is to be the leader of regional information and communications group, offers a comprehensive range of communication services and solutions in fixed line, mobile, data and broadband. Therefore the objectives of this research are to determine the factors that influenced the rebranding strategy of TM several variables such the marketing mix tools (product, price, promotion and place), market dominance and competition. Two approaches of collecting data are being used. The first approach is primary data such as questionnaires while the second approach is secondary data such as TM Annual Report, Magazines, pamphlets, textbook, journals and Internet (external data). From the findings, it was concluded that majority of the respondents ( TM's staff) have agreed that product, price, promotion and place, competition and market dominance are the factors that influence the rebranding strategy. The outcome of this research is important in creating a strategy corporate image in the eyes of the customers. By determining these factors it is hoped that the customers will be more loyal and satisfied with TM services

Surgical and non-surgical prosthetic hands control: a review

This paper concerns on the review between the surgical and non-surgical method of active control of a prosthetic hand. For active prosthetic hand, there are two standard methods for signal extraction namely surgical and non-surgical. Active prosthetic hands which are based on Surface Electromyography (sEMG) and Targeted Muscle Reinnervation (TMR) are selected for a comparison between non-surgical and surgical type respectively. We made a review on the characteristics and procedures of the surgical and non-surgical prosthetic hand technique. The compatibility of the surgical and non-surgical method to the type of upper extremity amputations also discussed to propose a guide and baseline for the future design consideration for our future prosthetic hand design

Wound healing assessment using digital photography: a review

Digital photography as a non-invasive, simple, objective, reproducible, and practical imaging modality has been investigated for the wound healing assessment over the last three decades, and now has been widely used in clinical daily routine. Advances in the field of image analysis and computational intelligence techniques along with the improvements in digital camera instrumentation, expand the applications of standardized digital photography in diagnostic dermatology such as evaluation of tumours, erythema, and ulcers. A series of digital images taken at regular intervals carries the most informative wound healing indexes, color and dimension, that may help clinicians to evaluate the effectiveness of a particular treatment regimen, to relieve patient discomfort, to globally assess the healing kinetics, and to quantitatively compare different therapies; however, the extent of underlying tissue damage cannot be fully detected. This paper is an introductory review of the important investigations proposed by researchers in the context of clinical wound assessment. The principles of wound assessment using digital photography were shortly described, followed by review of the related literature in four main domains: wound tissue segmentation, automated wound area measurement, wound three dimensional (3D) analysis and volumetric measurement, and monitoring and evaluation of wound tissue changes during healing

Characterization of surface electromyography using time domain features for determining hand motion and stages of contraction

Surface electromyography (SEMG) signals can provide important information for prosthetic hand control application. In this study, time domain (TD) features were used in extracting information from the SEMG signal in determining hand motions and stages of contraction (start, middle and end). Data were collected from ten healthy subjects. Two muscles, which are flexor carpi ulnaris (FCU) and extensor carpi radialis (ECR) were assessed during three hand motions of wrist flexion (WF), wrist extension (WE) and co-contraction (CC). The SEMG signals were first segmented into 132.5 ms windows, full wave rectified and filtered with a 6 Hz low pass Butterworth filter. Five TD features of mean absolute value, variance, root mean square, integrated absolute value and waveform length were used for feature extraction and subsequently patterns were determined. It is concluded that the TD features that were used are able to differentiate hand motions. However, for the stages of contraction determination, although there were patterns observed, it is determined that the stages could not be properly be differentiated due to the variability of signal strengths between subjects

Non-pharmacological treatment uptake for chronic musculoskeletal pain among community-dwelling older adults in Petaling district, Selangor

Introduction: Chronic musculoskeletal pain is a common disabling condition among older adults with the majority, remain undertreated. This study aimed to determine the uptake of non-pharmacological treatment for chronic musculoskeletal pain among older adults and the associated factors. Methods: A stratified sampling proportionate to size with individual clinics as the strata were used to recruit 276 respondents from six public health clinics in Petaling district, one of the most aged districts in the state of Selangor, Malaysia. Based on the proportion calculated, eligible older adults were selected by systematic random sampling from the registration list. Data was collected using a pre-tested and validated questionnaire through a face-to-face interview with respondents. The questionnaire comprised of seven sections, namely, socio-demographic, comorbidity, depression, pain severity, treatment options, attitude towards chronic pain and chronic musculoskeletal pain. Inferential analysis was conducted using Chi-Square (X2) and Fisher’s Exact Tests. The P value of < 0.05 regarded as statistically significant. Results: A total of 242 (87.7%) of the respondents had chronic musculoskeletal pain, in which 235 (85.1%) were treated with non-pharmacological treatments. The commonly used non-pharmacological treatments were exercise (67.8%), biological-based therapies (40.9%) and massage (33.7%). The uptake of non-pharmacological treatment for chronic musculoskeletal pain among older adults was significantly associated with the presence of diabetes. Conclusion: The findings revealed the remarkably high uptake of non-pharmacological treatment among older adults who experienced chronic musculoskeletal pain which was significantly associated with diabetes and the presence of other diseases like high blood pressure, osteoarthritis, back pain and rheumatic arthritis

Intelligent massage chair based on blood pressure and heart rate

Massage is one of the effective techniques used to relieve pain, reduce stress, and increase relaxation. Nowadays, massage methods have varied to an easier way by electronic massage chair massage which is able to control the massage mode according to specifications. Commercial massage chair can only be used on normal healthy people with no health complication, such as diabetes, heart problem or blood pressure problem. The purpose of this study is to develop a system of more advanced massage chair where it can have an impact on user health based on blood pressure and heart rate. The proposed massage chair equipped with blood pressure and heart rate sensors, where the therapy will automatically configured according to individual's blood pressure and heart rate readings. The proposed control system developed using the artificial intelligent of fuzzy logic for data classification. The complete model of this massage control system is then developed using SIMULINK software to simulate the whole system operation and verify the function as programmed. Upon the success of the investigation, the findings will be useful for rapid advances in the existing technology

Re-gripping analysis based on implementation of slip-detection device for robotic hand model

To develop an intelligent robotic hand, diverse approaches have been applied, including optimum gripping force and slippage analysis. In this study, a robotic hand was modeled with tactile pressure sensors. The slip detection sensor, which is represented as a rotary encoder device, was employed to indicate the slip situation features, distance and velocity. Empirical findings imply that the correlation between the distance that an object has slipped and the required re-gripping force was developed to be availed as an automatic feedback algorithm. The slippage events were revealed and analyzed to perform the control system mechanism of the re-gripping mission

New methodology of online sliding surface slope tuning PID like fuzzy sliding mode controller for robust control of robot manipulators

Designing a robust controller for uncertain multi input-multi output (MIMO) nonlinear dynamical system (e.g., robot manipulator) can be a challenging work in this research. Robot manipulators are set of links which connected by joints, they are multiple-input and multiple-output (MIMO), nonlinear, time variant, uncertain dynamic systems and are developed either to replace human work in many fields such as in industrial or in the manufacturing. According to the dynamic formulation of robot manipulators, they are uncertain and have strong coupling effects between joints. To solve this challenge, sliding mode controller is selected since it is robust, stable and it works very well in certain and fairly uncertain condition. Although this controller works incredibly efficient, but still, it has two important challenges, namely the high frequency chattering and working in uncertain situation. To reduce the chattering with respect to stability and robustness; linear controller is added to discontinuous (switching) part of sliding mode controller. In this methodology linear controller is used in parallel with discontinuous part to reduce the role of sliding surface slope and switching (sign) function. To modify chattering free sliding mode controller in uncertain situation PID like fuzzy logic theory is recommended in estimating the robot manipulator's nonlinear dynamic formulation and on-line tuning sliding surface slope.As a result, this controller improves the stability and robustness, reduces the chattering as well and reduces the level of energy due to the torque performance as well

P300-based EEG signal interpretation system for robot navigation control

In recent years, Brain-Computer Interface (BCI) research has provoked an enormous interest among researchers from different fields. The most popular approach is a non-invasive method, using Electroencephalogram (EEG) analysis which acquires signals from the brain. The aim of this project is to develop a brain signal interpretation system that can convert one thought into multiple movements for mobile robot navigation. A signal interpretation system is designed and developed to receive the EEG signal via User Datagram Protocol (UDP) transmission, converts the signal to several robot commands that are pre-programmed according to the robot’s programming software and send the commands to the robot through the operating computer. Using signals from four electrodes to evaluate the signal interpretation system, a success rate of 75-80% is received, while a total response time of only 61 seconds needed by the system from the start of the stimuli until the robot has finished all commands sent by the system, as compared to the conventional method of one-thought-one-movement which can take around 30 seconds per command. With this system, user can expect faster execution of the robot commands, less thinking therefore less exhausting, making BCI a pleasant experience for all users regardless of their health conditions