# Artificial Neural Network Analyzing Wearable Device Gait Data for Identifying Patients With Stroke Unable to Return to Work

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/artificial-neural-network-analyzing-wearable-device-gait-data-for-identifying/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Marco Iosa,E Capodaglio,Silvia Pelà,Benedetta Persechino,Giovanni Morone,Gabriella Antonucci,Stefano Paolucci,Monica Panigazzi |
| Citations | 42 |
| DOI | 10.3389/fneur.2021.650542 |
| Fields | Health Professions,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.frontiersin.org/articles/10.3389/fneur.2021.650542/pdf |
| OpenAlex ID | https://openalex.org/W3163280239 |
| PMID | 34093396 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Benedetta Persechino](https://scholariq.org/researchers/benedetta-persechino/)

## Paper journal

- [Frontiers in Neurology](https://scholariq.org/journals/frontiers-in-neurology/)

## Paper primary topic

- [Stroke Rehabilitation and Recovery](https://scholariq.org/topics/stroke-rehabilitation-and-recovery/)

## Paper topics

- [Stroke Rehabilitation and Recovery](https://scholariq.org/topics/stroke-rehabilitation-and-recovery/)
- [Balance, Gait, and Falls Prevention](https://scholariq.org/topics/balance-gait-and-falls-prevention/)
- [Acute Ischemic Stroke Management](https://scholariq.org/topics/acute-ischemic-stroke-management/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.