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AI Plush ToyMedTech & Wearables
HealthCare Pediatrics
ZenSloth: Bio-responsive Emotional Support Companion
IoT-enabled plush sloth with bio-sensors for real-time anxiety detection and haptic heartbeat feedback.
Heartbeat Sync
98%
Battery Life
14 Days
HealthCare Pediatrics
Plan A — Quick Facts
MCU Platform
Nordic nRF5340 dual-core (128MHz + 64MHz)
Sensor Type
Capacitive ECG + impedance respiratory
Signal Quality
Medical-grade AFE with 24-bit ADC
Haptic Engine
LRA linear resonant actuator, 40-300Hz
ML Classifier
TinyML anxiety detection model (12KB)
Wireless
Bluetooth LE 5.3 with companion app
Washability
IPX4-rated electronics pod, removable
Battery
950mAh Li-Po, 14 days standby
Certifications
CE, FCC, IEC 62368-1 safety
Overview
We integrated non-invasive capacitive ECG and respiratory sensors into a huggable sloth plush toy. An internal haptic engine uses machine learning algorithms to analyze children's vital signs in real-time and produce synchronized soothing physical heartbeat feedback, effectively detecting and alleviating child anxiety.
Sensor Engineering
Custom flexible PCB with capacitive bio-electrodes woven into the fabric. The analog front-end achieves clinical-grade signal quality while remaining completely safe for children.
Embedded Software
A Nordic nRF5340 dual-core MCU runs the bio-signal processing pipeline on one core and BLE communication on the other. The ML classifier was trained on pediatric physiological datasets.
Results
Clinical trials showed 98% heartbeat synchronization accuracy and a measurable reduction in pediatric anxiety scores during hospital stays.
Deep Tech FAQ
How was custom hardware leveraged for HealthCare Pediatrics?+
By transitioning from generic hardware to a custom edge architecture, we significantly reduced processing latency and improved overall thermal and power efficiency.
What are the core technical benefits of this edge deployment?+
The primary benefits include real-time inference without cloud dependency, enhanced data privacy, and drastic reductions in operational bandwidth costs.
Can this architecture be adapted for other use cases?+
Absolutely. The underlying Neural Fabric Methodology used here is highly modular and can be retargeted for various industrial and enterprise edge applications.
Project Profile
Services Delivered
Hardware DesignEmbedded SoftwareAI/ML Engineering
Core Technologies
BLESignal ProcessingCMachine Learning
Silicon & Vendors
Nordic SemiconductorTexas Instruments
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