Multifingered robot hand robot operates using teleoperation

The purpose of research on anthropomorphic dextrous manipulation is to develop anthropomorphic dextrous robot hand which approximates the versatility and sensitivity of the human hand by teleoperation methods that will communicate in master– slave manners. Glove operates as master part and multi-fingered hand as slave. The communication medium between operator and multi-fingered hand is via KC-21 Bluetooth wireless modules. Multi-fingered hand developed using 5 volt, 298:1 gear ratio micro metal dc motors which controlled using L293D motor drivers and actuator controlled the movement of robot hand combined with dextrous human ability by PIC18F4520 microcontroller. The slave components of 5 fingers designed with 15 Degree of Freedom (DOF) by 3 DOF for each finger. Fingers design, by modified IGUS 07-16-038-0 enclosed zipper lead E-Chain® Cable Carrier System, used in order to shape mimic as human size. FLEX sensor, bend sensing resistance used for both master and slave part and attached as feedback to the system, in order to control position configuration. Finally, the intelligence, learning and experience aspects of the human can be combined with the strength, endurance and speed of the robot in order to generate proper output of this project

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

Closed-loop Functional Electrical Stimulation (FES) – cycling rehabilitation with phase control Fuzzy Logic for fatigue reduction control strategies for stroke patients

Functional Electrical Stimulation (FES) cycling, or FES-Cycling, holds great therapeutic potential for individuals with paralysis, such as those with Spinal Cord Injury (SCI), traumatic brain injury, or stroke, aiming to restore mobility. However, the nonlinear nature of the musculoskeletal system poses a significant challenge in controlling FES-Cycling. To address this, an integrated closed-loop phase angle fuzzy-based system was developed. This system offers real-time control by adjusting stimulation intensity (pulse width) within the range of 50 to 200μs while maintaining a constant frequency of 35Hz, thereby ensuring precise pedaling trajectory and cadence patterns. An experimental study involved three healthy individuals (Cases A, B, and C) and one individual with hemiplegia stroke (Case D). Results showed that the proposed system consistently reduced average angle trajectory errors for Cases A, B, and C, with values of 2.6945, 3.2958, and 2.9922 degrees, respectively. Case D, affected by hemiplegia stroke, faced greater challenges and exhibited a higher error of 3.4562 degrees. Fatigue resistance, evaluated through fatigue indices, showed promising results for Cases A, B, and C with values of 0.10778, 0.06866, and 0.04603, respectively. However, Case D experienced higher fatigue (0.2304) due to the unique challenges of hemiplegia stroke. These findings highlight the effectiveness of the proposed control system in optimizing FES-Cycling, particularly for healthy individuals. For individuals with paralysis, like Case D, further research is needed to adapt the system to their specific conditions and cycling patterns. This system holds the potential for enhancing FES-Cycling as a therapeutic strategy and warrants additional investigation and customization for different patient populations

Antibiotic-Nigella Sativa Fusion (ANF) as a novel approach intended for the treatment against bacteria forming biofilm in osteomyelitis

Multi-drug resistant bacteria are one of the global problems facing humanity. One of the bacteria of concern causing osteomylitis is Staphylococcus aureus. Biofilm from this bacterium in the infected bones has been clinically isolated from the infected patients. A novel formulation of a contemporary antibiotic i.e Gentamicin (an Aminoglycoside) was fused with prophetic medicine i.e Nigella Sativa oil (NSO) (also known as black seed oil) and thereafter characterised. The fusion was done by preparing the emulsions of the two materials with the aid of varying amount of surfactants. Compatibility testing of the two compositions was also conducted pre and post fusion and pre and post gamma irradiation by Fourier-Transform Infra Red (FTIR), HPLC and Thin Layer Chromatography (TLC). In-vitro efficacy test of the fusion was further tested against both the sensitive and the resistant of the commercial and the clinically isolated S.Aureus. Cell viability was also performed on osteoclast cells to determine preliminary safety profile of the fusion. Results indicate that the fusions are physically and chemically compatible and stable with significantly higher safety level than gentamicin alone. The fusions showed ability to inhibit biofilm formation and are also more effective in-vitro particularly against the resistant S.Aureus unlike Gentamicin. With further clinical proofs, the findings could have high impact on current treatment regimen against multi-drug resistant bacteria particularly for osteomyelitis. It is also pave the way for more antibiotics to be fused with NSO and perhaps other prophetic medicine and tested for the same purpose or others

Identification source of variation on regional impact of air quality pattern using chemometric

This study intends to show the effectiveness of hierarchical agglomerative cluster analysis (HACA), discriminant analysis (DA), principal component analysis (PCA), factor analysis (FA) and multiple linear regressions (MLR) for assessing the air quality data and air pollution sources pattern recognition. The data sets of air quality for 12 months (January–December) in 2007, consisting of 14 stations around Peninsular Malaysia with 14 parameters (168 datasets) were applied. Three significant clusters - low pollution source (LPS) region, moderate pollution source (MPS) region, and slightly high pollution source (SHPS) region were generated via HACA. Forward stepwise of DA managed to discriminate 8 variables, whereas backward stepwise of DA managed to discriminate 9 out of 14 variables. The method of PCA and FA has identified 8 pollutants in LPS and SHPS respectively, as well as 11 pollutants in MPS region, where most of the pollutants are expected derived from industrial activities, transportation and agriculture systems. Four MLR models show that PM10 categorize as the primary pollutant in Malaysia. From the study, it can be stipulated that the application of chemometric techniques can disclose meaningful information on the spatial variability of a large and complex air quality data. A clearer review about the air quality and a novel design of air quality monitoring network for better management of air pollution can be achieved