Powering the Future of Smart Healthcare through Electrical & Electronics Innovation.

I-PRISM equips EEE graduates to lead the next revolution in biomedical devices, energy-efficient hospitals, and smart healthcare systems.

Your Learning Journey at a Glance

What you may have learned:

➤Power systems, circuits, machines, control systems, embedded hardware, and electrical safety fundamentals.

What you may not know:

➤How electrical design, low-power systems, and bio-electrical interfaces are engineered for safe medical and therapeutic devices.

What you will learn:

➤To build medical-grade hardware, power-optimized clinical systems, and integrative therapeutic devices for PRISM clinics.

Basic Certification in PRISM

The PRISM Basic Certification is tailored for engineers and technologists, giving them biomedical and healthcare literacy from a systems perspective. Engineers are introduced to human biology, anatomy, physiology, and major medical conditions while learning how Vata-Pitta-Kapha concepts model homeostasis and system behaviour — offering new inspiration for innovation. They gain hands-on exposure to bio-signals, health datasets, and AI-based diagnostics such as digital pulse analysis and integrative telehealth platforms. The program enables engineers to speak both medical and technical language confidently, making them effective collaborators in emerging health-tech environments.

Who should join: ECE, EEE, CS/AI/ML, Mechatronics, Mechanical, Civil engineers — final-year students or early-career professionals interested in biomedical devices, digital health, or healthcare system innovation.

Outcomes
Apply engineering skills to healthcare innovation.
Work effectively with clinicians and biomedical teams.
Use PRISM digital tools and bio-signal analytics in real contexts.

Advanced Certification in PRISM

The Advanced Certification elevates engineers from skilled learners to innovators. Participants work on real-world healthtech solutions such as AI-based Nadi Pariksha devices, rehabilitation technologies, VR training tools, clinical data platforms, or decision-support systems embedding traditional medical knowledge. The curriculum features computational modelling, multi-omic data analytics, and entrepreneurial deployment strategies — including regulatory pathways and clinical readiness for medical devices and software. Engineers graduate with a prototype/portfolio and the capability to lead cross-disciplinary innovation in medtech.

Who should join: Students who completed the Basic program and who are already familiar with biomedical concepts who want to specialize in AI-driven healthcare, wearable/medical device engineering, robotics for therapy, or startup-led health innovation..

Outcomes
Become industry-ready healthtech innovators.
Build deployable prototypes and product concepts.
Use computational and systems-medicine models in design.

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Academic & Clinical Disciplines Covered in I-PRISM

EEEs understand signals but not organ systems. This module links physiology with biosignals.
Learning Objective: Learn cardiovascular, neurophysiology, biomechanics and meaning of biosignal origins.
Integration: Enables designing sensors and wearables placed optimally to capture accurate ECG/EEG/pulse-wave data.

EEEs understand micro/nano electronics but not biochemistry.
Learning Objective: Learn bioelectricity, ion gradients, metabolism markers, biochemical signaling.
Integration: Enables development of biochemical + electrical hybrid sensors (stress sweat analyzers, glucose biosensors, hormone-responsive circuits).

EEEs understand detecting anomalies in signals but not disease states.
Learning Objective: Learn how diseases alter biosignals, vitals and electrical activity.
Integration: Enables smart diagnostics that detect inflammation, metabolic disorders or emergencies from signal patterns.

Engineers know chemical sensors but not drug/phytochemical dynamics.
Learning Objective: Learn active compounds, dosage timing, and delivery mechanisms.
Integration: Enables development of smart herbal diffuser devices, dose-tracking dispensers and lab-on-chip quality testing of herbal extracts.

EEEs know implants and electrodes but not tissue healing technologies.
Learning Objective: Learn bioelectrical stimulation, wound-healing microcurrents, biomaterial monitoring.
Integration: Enables creation of sensors embedded in grafts and stimulators adjusting current based on tissue impedance.

EEEs know EEG algorithms but not mind-body physiological interpretation.
Learning Objective: Learn stress, HRV, breath signals and neural markers of relaxation.
Integration: Enables meditation headsets, HRV-guided breath devices, and frictionless biofeedback apps linked to yoga/mindfulness.

EEEs know connectivity and IoT but not telehealth clinical requirements.
Learning Objective: Learn secure medical data, HIPAA-style protocols, remote vitals integration.
Integration: Enables telehealth platforms collecting sensor data (ECG, pulse, BP) directly into digital clinical dashboards.

EEEs know ML but not clinical datasets.
Learning Objective: Learn outcome prediction, integrative symptom encoding, biomedical feature engineering.
Integration: Enables AI tools that combine ECG/HRV/tongue-scan/pulse-wave to support integrative diagnosis and therapy recommendations.

EEEs know electronics but not multi-modality diagnostic workflow.
Learning Objective: Learn sequencing, prioritization and usability of diagnostic evaluations.
Integration: Enables unified diagnostic devices capturing vitals + imaging + traditional diagnostics in one interface.

EEEs know robotics/power systems but not therapeutic physics.
Learning Objective: Learn mechanisms behind TENS, ultrasound, PEMF, laser and vibration modalities.
Integration: Enables development of next-gen therapy systems (acupressure robots, smart PEMF beds, IoT-integrated physiotherapy machines).

EEEs collaborate well with engineers, not clinicians.
Learning Objective: Learn real constraints of clinics: time, simplicity, alarms, patient safety, low-button UI.
Integration: Engineers redesign devices to be intuitive, safe and clinical-workflow friendly.

EEEs know patents and technical testing but not clinical validation.
Learning Objective: Learn device trial design, regulatory pathways (FDA/CE), safety compliance and global market adaptation.
Integration: Produces devices that are validated clinically, compliant legally, and scalable worldwide.

Application Process

Stage – 1

Eligibility & Application

Applicants provide GATE score (preferred) or strong CGPA with portfolio of relevant tech projects, along with CV, SOP, and academic transcripts.

Stage – 2

Score Normalization

Academic Index is computed by standardizing graduation marks and entrance score (if available) to ensure fair merit evaluation.

Stage – 3

ISAT Examination

Engineering-specific ISAT section evaluates branch fundamentals (e.g., DSA, circuits, signals, mechanics) and ability to apply technology to healthcare.

stage – 4

Shortlisting

Shortlisting is based on CPIS ranking, balancing academic performance with analytical and technical aptitude.

stage – 5

Interview

Panel assesses innovation mindset, practical problem-solving, portfolio quality, and readiness to translate engineering into health-tech solutions.

stage – 6

Final Selection

Final Selection Score combines academic merit, ISAT percentile, and interview evaluation to determine admission offers.

stage -7

Enrollment & Bridging

Selected candidates complete bridging modules in human biology, anatomy, and physiology to prepare for healthcare-focused coursework.

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