Name
Abstract | ||
|---|---|---|
Continuous remote monitoring with convenient wireless sensors is attractive for early detection of patient deterioration, preventing adverse events and leading to better patient care. This article presents an innovative sensor design of VitalPatch, a fully disposable wireless biosensor, for remote continuous monitoring, and details the performance assessments from bench testing and laboratory validation in 57 subjects. The bench testing results reveal that VitalPatch's QRS detection had a positive predictive value of $> 99$% from testing with ECG databases. The accuracies of HR, BR and skin temp (in mean absolute error, MAE) from bench testing were $< 5$ bpm, $< 1$ brpm, $< 1 ^{ \circ}C$ respectively. The laboratory testing in 57 subjects revealed the accuracy of HR and BR to be $2.2 \pm 1.5$ bpm and $1.7 \pm 0.7$ brpm respectively for stationary periods. The absolute percent error in detecting steps was $4.7 \pm 4.6$%, and the accuracy in detecting posture was $96.4 \pm 3.1$%. Meanwhile, the specificity and sensitivity of fall detection $( \mathrm {n}=20)$ was found to be 100% and 93.8%, respectively. In conclusion, VitalPatch biosensor demonstrated clinically acceptable accuracies for its vital signs and actigraphy metrics applicable for continuous unobtrusive patient monitoring. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/EMBC.2018.8512569 | EMBC |
Field | DocType | Volume |
Biomedical engineering,Computer vision,Early detection,Wireless,Remote patient monitoring,Computer science,Mean absolute error,Continuous monitoring,QRS complex,Patient care,Artificial intelligence,Laboratory testing | Conference | 2018 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nandakumar Selvaraj | 1 | 12 | 3.53 |
| Gabriel Nallathambi | 2 | 0 | 1.01 |
| Rod Moghadam | 3 | 0 | 0.34 |
| Arshan Aga | 4 | 0 | 0.34 |