Evidence map›Paper›PMID 40732618›Full record

ArticleSensors (Basel, Switzerland)2025

SmartBoot: Real-Time Monitoring of Patient Activity via Remote Edge Computing Technologies.

Gozde Cay, Myeounggon Lee, David G Armstrong, Bijan Najafi

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Gozde CayDigital Health and Access Center (DiHAC), Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX 77030, USA.ORCID 0000-0003-1985-1772
Myeounggon LeeDigital Health and Access Center (DiHAC), Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX 77030, USA.ORCID 0000-0001-8546-5613
David G ArmstrongSouthwestern Academic Limb Salvage Alliance (SALSA), Department of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA.ORCID 0000-0003-1887-9175
Bijan NajafiDigital Health and Access Center (DiHAC), Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX 77030, USA.ORCID 0000-0002-0320-8101

Funding

Improving the science of adherence reinforcement and safe mobility in people with diabetic foot ulcers using smart offloadingR01DK124789 · NIDDK · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ARMSTRONG, DAVID GEORGE, NAJAFI, BIJAN · 2021 to 2025
$2.0M
NIDDK NIH HHS R01 DK124789NIH HHS 1R01DK124789-01A1
6 · The paper itself

Abstract

Diabetic foot ulcers (DFUs) are a serious complication of diabetes, associated with high recurrence and amputation rates. Adherence to offloading devices is critical for wound healing but remains inadequately monitored in real-world settings. This study evaluates the SmartBoot edge-computing system-a wearable, real-time remote monitoring solution integrating an inertial measurement unit (Sensoria Core) and smartwatch-for its validity in quantifying cadence and step count as digital biomarkers of frailty, and for detecting adherence. Twelve healthy adults wore two types of removable offloading boots (Össur and Foot Defender) during walking tasks at varied speeds; system outputs were validated against a gold-standard wearable and compared with staff-recorded adherence logs. Additionally, user experience was assessed using the Technology Acceptance Model (TAM) in healthy participants (n = 12) and patients with DFU (n = 81). The SmartBoot demonstrated high accuracy in cadence and step count across conditions (bias < 5.5%), with an adherence detection accuracy of 96% (Össur) and 97% (Foot Defender). TAM results indicated strong user acceptance and perceived ease of use across both cohorts. These findings support the SmartBoot system's potential as a valid, scalable solution for real-time remote monitoring of adherence and mobility in DFU management. Further clinical validation in ongoing studies involving DFU patients is underway.

Indexed as

Diabetic FootMonitoring, AmbulatoryWearable Electronic DevicesAdultAgedFemaleHumansMaleMiddle AgedMonitoring, PhysiologicWalkingadherencediabetic foot ulcerdigital healthedge computingoffloadingpersonalized careremote patient monitoringsmart footweartelemedicinewearableswound care

Identifiers

PMID40732618
PMCPMC12299288

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.