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Our Research and Patents
The Shift Methodology
The SHIFT methodology is a transformative approach to social innovation and product development, designed to address complex societal challenges through a structured, human-centered process. Employed by organizations like Punarjeeva, SHIFT emphasizes a deep understanding of community needs, fostering empathy and collaboration to create impactful solutions. By integrating diverse perspectives and iterative design principles, this methodology not only enhances the effectiveness of social initiatives but also ensures that products and services are tailored to the unique contexts they serve. Through its comprehensive framework, SHIFT empowers organizations to drive meaningful change and sustainable development in the social impact sector.
Punarjeeva Research
Punarjeeva has been working closely with the Neuro-divergent, Cerebral Palsy, Stroke Rehabilitation research for the past 5 years. We have created various first of its kind research based products for Persons with Disability (PwD). Our research has been focussed on the following:​
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Game Therapy (Augmented Reality and Gesture Recognition) based Platforms for improving physical movement
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Fine Motor improvement research using technology (Internet of Things and Artificial Intelligence)
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Gross Motor focussed products (Technologies include Full Body tracking with Sensor Hub)
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Virtual Reality (VR) therapy research
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Research for improving mindfulness and specifically for ADHD
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Brain Wave Analytics Research (Technology: Brain Computer Interface)
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Bio-Feedback enabled Technology Research
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Blended Learning Research (Agri-Therapy and Technology)
Patent
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The patent “SYSTEM FOR ADAPTIVELY AND INTELLIGENTLY PROVIDING TASKS TO A USER” has been granted in the India Jurisdiction.
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Patent Number: 410770
Research Papers
Sustainability Modelling for Employment‑focused Training Ecosystems for Young Adults with Disabilities
Ravindranathan, R. ., Usha, S., Tommy, R. ., & George, S. R. . (2024)
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This insightful study explores an innovative training ecosystem designed for neurodivergent young adults—integrating technology-assisted skill assessment, a structured 5D clarity training curriculum, and a gig-economy framework. With mixed-methods analysis, the authors demonstrate that participants show marked improvements in digital skills and high employment placement rates shortly after program completion, showcasing a sustainable model that addresses significant employment barriers.
Abstract
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Background: Neurodivergent young adults face significant employment challenges globally, with unemployment rates reaching 80% in India. This study examines an innovative employment-focused training ecosystem for neurodivergent individuals, incorporating technological interventions and a gig economy model. Neurodivergent individuals are those whose brain functions differently in one or more ways than is considered standard or typical.
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Methods: A mixed-methods approach was employed, combining quantitative analysis of program outcomes with qualitative insights from stakeholders. The study utilized technology interventions for skill assessment, implemented a 5D clarity process-based training curriculum, and integrated a gig economy framework.
Results: The study demonstrated notable success in employment outcomes, with a significant proportion of participants securing work within months of completion. Participants reported substantial gains in digital skills acquisition. Technological interventions for assessments revealed unique strengths in individuals that were not apparent through traditional methods. The gig economy model showed promise in providing flexible, suitable employment options for neurodivergent individuals.
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Conclusions: The innovative ecosystem demonstrates significant potential in creating sustainable employment opportunities for neurodivergent individuals, addressing key gaps in traditional training and employment models.
Interest and Skill Correlation Model for Career Aligning of Young Persons with Disabilities
Ravindranathan, R. ., Usha, S., Tommy, R. ., & George, S. R. . (2024)
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Persons with disabilities face significantly higher unemployment rates due to workplace biases and the limitations of traditional career assessment tools, which often fail to capture the unique cognitive strengths of neurodiverse individuals. Advances in neuroscience and neurotechnology, particularly electroencephalography (EEG), provide an opportunity to develop objective, data-driven frameworks for identifying individual aptitudes. This study introduces an EEG-based assessment model that analyzes task-related brain activity to map neurocognitive profiles to suitable career paths and corresponding skill sets. By leveraging neurodiversity profiling and cognitive strength mapping, this approach aims to enhance career guidance, employment inclusion, and workplace accessibility, ultimately promoting social equity and improved quality of life for persons with disabilities.
Abstract
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Background: Persons with disabilities of working age often encounter unemployment rates 2-3 times higher than their non-disabled peers, primarily due to workplace biases and a lack of personalized career guidance. Traditional assessment methods often fail to capture the unique strengths of neurodiverse individuals, leading to job mismatches and underemployment.
Objective: This study proposes an innovative framework using neuroscience-based assessments, specifically electroencephalography (EEG), to objectively evaluate the aptitude and strengths of persons with disabilities. The primary objective is to establish a data-driven model that correlates task-related brain activity patterns with suitable job opportunities and the necessary skill sets.
Methodology: The methodology involves conducting EEG assessments during various cognitive tasks, analyzing the resulting data to identify individual strengths, and mapping these strengths to potential career paths. The model categorizes individuals into neurodiversity profiles based on their specific disability conditions
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and their neurological responses during these assessments. This approach allows for a more nuanced understanding of each individual's capabilities, moving beyond traditional assessment methods that may not fully capture the strengths of neurodivergent individuals.
Objective: The EEG-based assessment model demonstrates the potential for more accurately identifying cognitive strengths in neurodiverse individuals compared to traditional methods. By utilizing neurotechnology to align individual capabilities with suitable employment paths, this approach aims to significantly boost workplace inclusion, personal autonomy, and social equality for persons with disabilities. This approach has the potential to revolutionize career guidance for persons with disabilities, leading to higher employment rates, improved job satisfaction, and better overall quality of life.
The Impact of Gamified Therapy on Physical, Cognitive, & Emotional Outcomes in Children with Cerebral Palsy: A Case Study Analysis
Tommy, R. ., Badrinarayanan, M. ., George, S. R. ., & Ravindranathan, R. . (2024)
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Cerebral palsy (CP) is a complex neurological disorder that affects movement, coordination, and cognitive development in children. Conventional therapies often face challenges related to limited engagement and poor adherence. To address these issues, this study explores a gamified therapeutic approach developed using the SHIFT Framework, designed to enhance motivation, participation, and overall treatment effectiveness. By integrating game-based elements and personalized interactions, the intervention aims to make rehabilitation more engaging while improving motor, cognitive, and emotional outcomes for children with CP.
Abstract
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Background: Cerebral palsy (CP) is a neurological disorder affecting motor, cognitive, and social development in children. Traditional therapies often struggle with engagement and adherence. This study evaluates a novel gamified treatment developed with the SHIFT Framework to improve outcomes in children with CP.
Methods: A case study design assessed the effects of gamified therapy on seven children with various types and severities of CP. The intervention used the SHIFT Framework to include engaging game elements and customizable features. Assessments before and after the intervention measured hand-eye coordination, balance, motor skills, cognitive engagement, motivation, and emotional well-being using appropriate statistical methods..
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Results: Post-intervention, all cases showed improved motor skills, coordination, balance, cognitive engagement, and emotional states. Increased levels of attention, motivation, and persistence were noted, alongside enhanced therapy engagement. Statistical analysis revealed significant improvements (p<0.05) in most parameters.
Conclusion: The gamified therapy approach using the SHIFT Framework effectively enhanced physical, cognitive, and emotional outcomes for children with CP. The engaging, personalized intervention improved motivation, adherence, and functional outcomes, particularly in cognitive aspects relevant to intellectual disabilities associated with CP. Further studies with larger cohorts and extended follow-ups are necessary to confirm these results and expand on the therapy’s applicability in CP management.
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Results: Our analysis revealed limitations in traditional therapies, including lack of engagement, limited personalization, and insufficient progress tracking. The proposed technology-driven solution shows potential for enhancing motivation, customization, and measurable progress in CP rehabilitation.
Conclusions: Our proposed digital platform offers promising avenues for improving rehabilitation outcomes and patient experiences by addressing key limitations in current CP therapy.
Assessing Current Cerebral Palsy Therapy and Identifying Needs for Improvement
Tommy, R. ., Badrinarayanan, M. ., Ravindranathan, R. ., & George, S. R. (2024).
Cerebral palsy (CP) is the most common childhood physical disability, often requiring long-term, intensive rehabilitation to improve motor function and quality of life. However, conventional therapy methods frequently struggle to sustain engagement, adapt to individual needs, and provide quantifiable progress tracking. With the growing potential of digital health technologies, integrating gamification, virtual reality (VR), and AI-based motion tracking offers an innovative pathway to enhance therapy experiences. This study explores current challenges in CP rehabilitation and proposes a technology-driven therapeutic platform designed to improve motivation, personalization, and measurable outcomes for children with CP.
Abstract
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Background: Cerebral palsy (CP) is a prevalent childhood physical disability requiring long-term therapeutic interventions. Conventional rehabilitation methods face challenges maintaining engagement and providing personalized, measurable outcomes.
Methods: This study assessed current CP therapy approaches through a literature review and primary data analysis. We propose an innovative digital therapeutic platform integrating gamification, virtual reality, and AI-based motion tracking.
Experimental VALidation of findings using BCI in Autistic kids- (EVAL BCI)
Ravindranathan, R. ., Tommy, R. ., & Athira Krishnan R (2020).
Cerebral palsy (CP) is the most common childhood physical disability, often requiring long-term, intensive rehabilitation to improve motor function and quality of life. However, conventional therapy methods frequently struggle to sustain engagement, adapt to individual needs, and provide quantifiable progress tracking. With the growing potential of digital health technologies, integrating gamification, virtual reality (VR), and AI-based motion tracking offers an innovative pathway to enhance therapy experiences. This study explores current challenges in CP rehabilitation and proposes a technology-driven therapeutic platform designed to improve motivation, personalization, and measurable outcomes for children with CP.
Abstract
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Autism is a developmental disorder that impairs the ability of affected to communicate and interact. This disease impacts the nervous system, resulting in poor emotional, social, cognitive and physical health. Affected ones are however capable of excelling in some or other field of their interest. To identify their interest, they need to be exposed to wide range of activities on a daily basis. Manual interpretations can go wrong as a person can complete a task with interest, fear, etc. Brain Computer Interface (BCI), helps read and analyze the human brain activity using brain waves. Attention values and brain waves from samples are analyzed while performing activities as part of experiment. So in this study using BCI, manually interpreted sample's interest to a task is verified experimentally. It is learnt that, samples show an improved percentage attention during sessions of their favourite task.
Presented the paper “Emerging Technology Solutions for Autistic Children” at the WAVES Kerala Summit – 2021. The conference was organized by the State Commissionerate for Persons with Disabilities, Government of Kerala, Composite Regional Centre for Persons with Disabilities and Able world.