**** Daphnet Freezing of Gait Dataset in users with Parkinson's disease ****

The Daphnet Freezing of Gait Dataset Freezing of Gait in users with Parkinson disease (hereafter Daphnet Freezing of Gait Dataset) is a dataset devised to benchmark automatic methods to recognize gait freeze from wearable acceleration sensors placed on legs and hip. The dataset was recorded in the lab with emphasis on generating many freeze events.

It is the result of a collaboration between the Laboratory for Gait and Neurodynamics, Tel Aviv Sourasky Medical Center, Israel and the Wearable Computing Laboratory, ETH Zurich, Switzerland. Recordings were run at the Tel Aviv Sourasky Medical Center in 2008. 

This dataset was collected as part of the EU FP6 project Daphnet, grant number 018474-2.
Additional effort to publish this dataset was supported in part by the EU FP7 project CuPiD, grant number 288516.

LICENCE
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Use of this dataset in publications must be acknowledged by referencing the following publication [1]. We also appreciate if you inform us (droggen@gmail.com) of any publication using this dataset for cross-referencing purposes.

Reference [1] describes the dataset in details. It explain the data acquisition protocol, the kind of sensor used and their placement, and the nature of the data acquired. It also provides baseline results for the automated detection of freezing of gait, against which newer methods can be benchmarked. In particular it describes detection sensitivity/specificity for 3 sensor placements and 4 kinds of derived sensor signals, it analyzes detection latency, and provides first insight into user specific v.s. user independent performance.

[1] Wearable Assistant for Parkinsons Disease Patients With the Freezing of Gait Symptom, Marc Bchlin, Meir Plotnik, Daniel Roggen, Inbal Maidan, Jeffrey M. Hausdorff, Nir Giladi, and Gerhard Trster, IEEE Transactions on Information Technology in Biomedicine, 14(2), March 2010, pages 436-446
