Hospital systems
Integrations
Every SoleGuard scan flows into the patient's chart and the care team's workflow — no manual data entry.
Epic Hyperspace
EHR · St. Mary's instance
Also configured: Cerner Millennium · Athenahealth · MEDITECH Expanse
Referral & alerts
High-risk patients routed to podiatry automatically
High-risk alert sent to Dr. Mensah
Patient: Elena Ramírez · Score 72 · refer to podiatry within 72h
Workflow status
Drafted
09:41:20
Sent to podiatry queue
09:41:22
Acknowledged by Dr. Mensah
09:41:48
- 4
Appointment scheduled
pending
Standards-based exchange
FHIR Observation resource
Every scan is serialized as a FHIR R4 Observation with the pressure peak as valueQuantity and ulcer-risk + hotspot as components. Compatible with any FHIR-enabled EHR and the SMART on FHIR app launch.
- LOINC 80394-6 · plantar pressure peak
- Bound to Patient and Device references
- HL7 v2.5 ORU^R01 also supported
- Signed with OAuth 2.0 client credentials
{
"resourceType": "Observation",
"id": "soleguard-obs-2087421",
"status": "final",
"category": [
{
"coding": [
{
"system": "http://terminology.hl7.org/CodeSystem/observation-category",
"code": "exam",
"display": "Exam"
}
]
}
],
"code": {
"coding": [
{
"system": "http://loinc.org",
"code": "80394-6",
"display": "Plantar pressure peak"
}
]
},
"subject": {
"reference": "Patient/elena-ramirez",
"display": "Elena Ramírez"
},
"effectiveDateTime": "2026-06-29T14:32:11Z",
"performer": [
{
"reference": "Device/soleguard-pad-A7"
}
],
"valueQuantity": {
"value": 287,
"unit": "kPa",
"system": "http://unitsofmeasure.org",
"code": "kPa"
},
"interpretation": [
{
"coding": [
{
"system": "http://terminology.hl7.org/CodeSystem/v3-ObservationInterpretation",
"code": "H",
"display": "High"
}
]
}
],
"component": [
{
"code": {
"text": "Ulcer risk score (SoleGuard AI)"
},
"valueQuantity": {
"value": 72,
"unit": "score"
}
},
{
"code": {
"text": "Pressure-time integral"
},
"valueQuantity": {
"value": 142,
"unit": "kPa·s"
}
},
{
"code": {
"text": "Hotspot location"
},
"valueString": "2nd metatarsal head, right foot"
}
]
}Subjects
39
Features
24
Folds
5
LR · AUC
0.74
RF · AUC
0.88
GBM · AUC
0.90
Top 5 features (standardized coefficient)
- Contact area · Midfoot+1.22
- Peak pressure · Midfoot+0.68
- Peak pressure · Heel lateral-0.59
- Peak pressure · Meta3+0.55
- Peak pressure · Toe1+0.44
Inference runs entirely on-device using a 24-coefficient logistic regression exported from scikit-learn. The classifier predicts flatfoot vs normal arch — a contributing biomechanical signal, not a substitute for clinical diagnosis. Cross-validated on a small single-sex cohort; broader validation is on the roadmap.
All payloads on this page use mock data for demonstration. No PHI is transmitted.