Automated Organization ProfileDepartment of Neurology, Helsinki University Hospital and Department of Clinical Neurosciences
Department of Neurology, Helsinki University Hospital and Department of Clinical Neurosciences
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets in this organization
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the organization's datasets
Total Mentions
Total mentions of the organization's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 2.1 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This is the raw wearable dataset from the paper by the authors, titled "Feasibility and patient acceptability of a commercially available wearable and a smartphone application in identification of motor states in Parkinson’s disease", PLOS Digital Health 2023, DOI 0.1371/journal.pdig.0000225 The HDF5 file has groups as subjects, P_* denoting patients and C_* denoting controls. Within each group, index "1" denotes accelerometer data, other indices are heart rate and other data not used in the study. For example, /P_fd3e/1/timestamp is the timestamp of the accelerometer data of (anonymized) patient P_fd3e, and /P_fd3e/1/y are their corresponding values measured from the y-channel of the device.
Authors
- Sammeli Liikkanen ;
- Sinkkonen, Janne ;
- Suorsa, Joni ;
- Kaasinen, Valtteri ;
- Pekkonen, Eero ;
- Kärppä, Mikko ;
- Scheperjans, Filip ;
- Huttunen, Teppo ;
- Sarapohja, Toni ;
- Ullamari Pesonen ;
- Kuoppamäki, Mikko ;
- Keränen, Tapani
This is the raw wearable dataset from the paper by the authors, titled "Feasibility and patient acceptability of a commercially available wearable and a smartphone application in identification of motor states in Parkinson’s disease", PLOS Digital Health 2023, DOI 0.1371/journal.pdig.0000225 The HDF5 file has groups as subjects, P_* denoting patients and C_* denoting controls. Within each group, index "1" denotes accelerometer data, other indices are heart rate and other data not used in the study. For example, /P_fd3e/1/timestamp is the timestamp of the accelerometer data of (anonymized) patient P_fd3e, and /P_fd3e/1/y are their corresponding values measured from the y-channel of the device.
Authors
- Sammeli Liikkanen ;
- Sinkkonen, Janne ;
- Suorsa, Joni ;
- Kaasinen, Valtteri ;
- Pekkonen, Eero ;
- Kärppä, Mikko ;
- Scheperjans, Filip ;
- Huttunen, Teppo ;
- Sarapohja, Toni ;
- Ullamari Pesonen ;
- Kuoppamäki, Mikko ;
- Keränen, Tapani