Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Interactive visualization of sensor and self-reported data of patients with Parkinson’s disease
Linnéuniversitetet.ORCID iD: 0000-0001-6745-4398
Örebro University.ORCID iD: 0000-0002-2372-4226
2019 (English)In: MIRAI AGEING Seminar, November 13-14, 2019, Stockh, 2019Conference paper, Poster (with or without abstract) (Other academic)
Abstract [en]

Advancements in telemedicine have been helpful for frequent monitoring of patients with Parkinson’s disease (PD) from remote locations and assessment of their individual symptoms and treatment-related complications. These data can be useful for helping clinicians and patients to interpret symptom states and individually tailor the treatments by visualizing the physiological information collected by sensor-based systems as well as patient self-reported states. Here we present various visualization and interaction techniques to help physicians explore patient’s daily activities, which could be useful for guiding them during the decision-making process. An interface is designed to visualize symptom and medication information, collected by an Internet of Things-based system comprising of a smartphone, electronic dosing device, wrist sensor and a bed sensor.

Place, publisher, year, edition, pages
2019.
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:bth-23903OAI: oai:DiVA.org:bth-23903DiVA, id: diva2:1710756
Conference
MIRAI AGEING Seminar, November 13-14, 2019, Stockholm
Available from: 2022-11-14 Created: 2022-11-14 Last updated: 2022-11-14Bibliographically approved

Open Access in DiVA

No full text in DiVA

Authority records

Jusufi, Ilir

Search in DiVA

By author/editor
Jusufi, IlirMemedi, Mevludin
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 3 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf