Browsing by Author "Desabhotla, Krishna Sarvani"
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Item Automation Process of 3D Scan Based Brace Design(2020-09-29) Desabhotla, Krishna Sarvani; Steele, Alexander G.; Eguren, DavidApproximately 83,700 children across the United States and 1.7 million children worldwide are affected by cerebral palsy and have limited or no walking ability. [1] Customizable exoskeletons could greatly improve rehabilitation outcomes and quality of life for children suffering from diseases such as cerebral palsy and spina bifida which limit mobility. Currently, it takes an expert 5-6 hours to create a single set of exoskeleton braces from one 3D scan imported into SolidWorks. In this project, we developed a process that enables braces created from a template 3D scan to readjust to another with minimal steps. This is critical as the braces must be modified as children grow. The process of solid modelling typically involves orienting objects, such as the braces, in reference to 3D space. Instead, by defining the braces using global variables and joint references like the hip, knee, and ankle, braces can transfer from the template scan to another scan with automatic size and orientation adjustment. The methodology of brace transfer involves changing the reference surface and joint of the template brace from one scan to another and can be done within minutes. This technique standardizes the design and drastically shortens the time it takes to create custom-fitted braces while reducing human error. Future work would expand the proof of concept to create a complete set of braces that transfers between scans. Applications for this research are not limited to exoskeletons but can be applied to any customizable 3D scan based orthotic/prosthetic. [1]https://www.cdc.gov/ncbddd/cp/data.htmlItem Towards a Gamified Therapeutic Brain-Computer Interface for Children with Gait Impairment(2022-06-13) Desabhotla, Krishna SarvaniCentral nervous system (CNS) disorders cause over 1 billion people to live with a life-altering handicap. Some CNS disorders, such as cerebral palsy and spina bifida, affect one-four per 1000 and one per 2758 children respectively, according to the Centers for Disease Control. These pediatric CNS disorders leave patients with many years of living with partial or complete motor impairment. Brain-computer interfaces (BCIs) have been researched as tools for rehabilitation for adults with disabilities due to neurological disease, brain injury or amputation; however, research on the design of BCI systems for children has not received the same level of attention by the scientific community. This is unfortunate as the developing brain is very plastic, thus, children may be the best candidates for BCIs for neurorehabilitation. The primary aim of this project was to adapt a system, developed in the Laboratory for Non-Invasive Brain-Machine Interface Systems at the University of Houston, that can be used for BCI system development for children. Such a system will provide real-time data capture from two types of sensors (scalp electroencephalography or EEG, and joint angle data from the lower limbs) during treadmill walking while providing real-time visual feedback of the child’s gait pattern via a digital avatar. To achieve this aim, a system was created in the MATLAB programming environment that initializes, acquires and synchronizes EEG and joint angles, and then, filters and sends joint angles to control the digital avatar and in parallel, stores time-locked unprocessed EEG and joint angle data for offline processing - the first step in designing a BCI system. Applications of the system include, but are not limited to, investigating the neural representations for motor control in children, and extracting neural and kinematic features for diagnostic purposes and for the design of closed-loop BCI systems for children.