NeuroCheck
AI
CLINICAL DEMO
Patent: AI-Based Assessment with Continuous Monitoring
Active
00:00:00
âš REC
Patient
Margaret Chen
MRN: 7742901 âĒ 74F âĒ BMI 22.1
NEURO ICU 4B
CFS 5
POST-OP DAY 2
Dx: L MCA aneurysm clipping
Hx: HTN, T2DM, mild cognitive impairment
Attending: Dr. C. Bowers, MD
Active Assessment
ð§
Cranial Nerve Testing
CN II â XII Automated
ð
Glasgow Coma Scale
Eye âĒ Verbal âĒ Motor
â ïļ
Delirium Screen
CAM-ICU-7 âĒ ICDSC âĒ RASS
ðĶī
Frailty Assessment
CFS âĒ TUG âĒ Sarcopenia
Camera Hardware
ICU CONFIGURATION â PER PATENT
âĒ
Bedside:
Intel RealSense D435i
Depth + RGB, 1280Ã720, 90fps
âĒ
Foot-of-Bed:
Axis M3068-P
12MP, 360° panoramic, IR
âĒ
Tablet:
iPad Pro TrueDepth
Portable bedside assessment
Edge compute: NVIDIA Jetson Orin Nano
Protocol: HL7 FHIR R4 + DICOM
LIVE â CAM 1: Bedside Intel RealSense D435i
30 FPS âĒ 468 landmarks âĒ CNN active
Initializing...
Starting assessment sequence
Face Detected â 468 Landmarks Tracked
Assessment: 0%
Live Scoring
Glasgow Coma Scale
â
Eye Opening (E)
â
Verbal Response (V)
â
Motor Response (M)
â
Cranial Nerves
0/10
CN II
CN III
CN IV
CN V
CN VI
CN VII
CN IX
CN X
CN XI
CN XII
CAM-ICU-7 Delirium
â
RASS Score
â
Acute Onset/Fluctuation
â
Inattention
â
Disorganized Thinking
â
Altered Consciousness
â
Frailty Index
â
Clinical Frailty Scale
â
Temporalis Wasting
â
Grip Strength Est.
â
Fall Risk (Hopkins)
â
ICU Room â Multi-Camera Configuration
ðïļ PATIENT
ð·
ð·
ð·
CAM 1: Bedside
Face + CN Testing
CAM 2: Foot-of-Bed
Full Body + Gait/TUG
CAM 3: Room
Gross Motor + Falls
PredictWell CommandOS Integration
1
Multi-camera captures video + depth + audio
CAPTURE
2
Edge AI: CNN movement + RNN/LSTM temporal
NEURAL NET
3
Assessment models: GCS, CN, CAM-ICU, CFS
SCORING
4
Results â PredictWell CommandOS dashboard
PLATFORM
5
EHR sync via HL7 FHIR R4 + Digital Health Binder
EHR
6
UPI longitudinal tracking + predictive analytics
OUTCOMES