A Tripod-Type Walking Assistance for the Stroke Patient

Kishore, P.S.; Dash, Anjan Kumar; Pragallapati, Akhil; Mugunthan, Dheerkesh; Ramesh, Aniirudh; Kumar, K. Dilip

doi:10.1007/978-981-33-6984-9_13

Cited by 5 publications

(1 citation statement)

References 7 publications

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“…Maintenance and initiation of specific protocols are other benefits in this respect. As a result, wrist rehabilitation utilizing robotics may be potentially improved with fewer challenges which could negatively impact patient satisfaction and outcomes [11], [12].…”

Section: Introductionmentioning

confidence: 99%

Machine learning and IoT Based Robotic Solution for Home Wrist Rehabilitation through Motion Capture Enabled Architecture

Ch. Gangadhar

2024

jes

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The present study investigates the effectiveness of an integrated approach that combines machine learning, robotic rehabilitation, and traditional methods for wrist rehabilitation among the hemiparesis population. Subjects with robotic rehabilitation at the four-week intervention period showed the ball’s significant difference in the flexion and extension angles and demonstrated the better overall outcomes from the robotic intervention . The machine learning models, in particular, the artificial neural networks, provided the prediction of rehabilitation outcomes and demonstrated the high accuracy, high precision, high recall, and high F1 score. This study supports the idea of the beneficial effects of combining robotic rehabilitation with machine learning algorithms and supports the notion that the two benefits could bring high synergistic effects above their individual potentials. The report also contributes to the development of the rehabilitation science of wrists, given that few studies have explored the applications of artificial intelligence methods or robotic rehabilitation beyond the context of feasibility reports. The findings of the current research could contribute useful insights for the decision-making practices of therapists and healthcare providers, also given the reliance on large data contributed by the previous interventions. Future study could investigate the long-term results, the cost-effectiveness of the approaches, and assist in developing the potential results of customization for individual patients.

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Section: Introductionmentioning

confidence: 99%

Machine learning and IoT Based Robotic Solution for Home Wrist Rehabilitation through Motion Capture Enabled Architecture

Ch. Gangadhar

2024

jes

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Optimizing Surface Roughness in Turning of Al7072 with nano particles of Carbon Metal Matrix Composite using Taguchi Analysis and ANN Prediction

Al Ansari,

Kaliappan,

Bhargavi

et al. 2024

E3S Web Conf.

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This research centers on optimizing the machining process of Al7072 alloy reinforced with carbon nanoparticles. While surface roughness is the primary research focus, it is one of the most critical parameters in the manufacturing of aerospace components. According to the Taguchi design of experiments tool, the structured experimental framework has been used to learn the precise consequences of Cutting speed (Cs) , Feed rate (Fr), and Depth of Cut (DoC) on surface roughness outcomes. Using cutting-edge algorithms, particularly the Artificial Neural Network, significantly increases these predictive abilities. It hence forecasts the surface roughness achieved with various machining outcomes. According to the initial results, the surface roughness response is extremely dependent on the machining outcomes. The signal-to-noise ratio conducted the statistical analysis to discover the best parameter equation that would allow for the best surface quality and machining economy. Furthermore, the ANN-based model has been created, demonstrating a high level of accuracy in providing feed response. This might be used to optimize the machining process. The results recommend improving the accessibility of machining and increasing aerospace equipment’s quality of service. Thus, the process presented in this research might improve the public’s communication with respect to machining and machining economics.

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Artificial Intelligence and Image Processing Techniques for Blood Group Prediction

Gupta

2024

2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT)

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A Tripod-Type Walking Assistance for the Stroke Patient

Cited by 5 publications

References 7 publications

Machine learning and IoT Based Robotic Solution for Home Wrist Rehabilitation through Motion Capture Enabled Architecture

Machine learning and IoT Based Robotic Solution for Home Wrist Rehabilitation through Motion Capture Enabled Architecture

Optimizing Surface Roughness in Turning of Al7072 with nano particles of Carbon Metal Matrix Composite using Taguchi Analysis and ANN Prediction

Artificial Intelligence and Image Processing Techniques for Blood Group Prediction

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