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This heart disease dataset is curated by combining 5 popular heart disease datasets already available independently but not combined before. In this dataset, 5 heart datasets are combined over 11 common features which makes it the largest heart disease dataset available so far for research purposes. The five datasets used for its curation are:
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When producing bolts in a cold forging process, the pressure signals are recorded per cycle of forming a bolt. The dataset is collected from experiments of different failure modes of a forming machine. Two experiments were recorded in csv format for providing four failure modes, including core broken, cavity block, insufficient lubrication, and material out-of-specification, as well as one normal mode. The two experiments were performed in the same machine with different cavities and cores, and saved in Experimental Data for Modeling and Testing.
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544 Views
This dataset is created with the usage of Galvanic Skin Response Sensor and Electrocardiogram sensor of MySignals Healthcare Toolkit. MySignals toolkit consists of the Arduino Uno board and different sensor ports. The sensors were connected to the different ports of the hardware kit which was controlled by Arduino SDK.
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The dataset contains:
- performance for random parameter values for the Embree datastructure on different scenes
- specific experiment data regarding the stability of triangle splitting, characterize by the angle of specific geometry
- partial tuning experiments, where parameters would be optimized while others would stay set
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91 Views
Data consists of an EMG registry obtained with a hybrid electrostimulation and electromyography device. Electrodes were placed to record activity from the extensor muscle of the fingers while the subject was squeezing a hand gripper for 10 seconds and resting for another 10.
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2984 Views
This dataset contains the output from 3D gait analysis. Over a period of 3 months, between January 1st and March 31st in 2019, 5 children were familiarized with the Hibbot by using the walking aid for 30 minutes, twice a week, under the supervision of a physiotherapist.
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218 Views
EmoSurv is a dataset containing keystroke data along with emotion labels. Timing and frequency data is recorded while participants are typing free and fixed texts before and after being induced specific emotions. These emotions are: Anger, Happiness, Calmness, Sadness, and Neutral state.
First, data is collected while the participant is in a neutral state. Then, the participant watches an eliciting video. Once the emotion is induced in the participant, he types another fixed and free text.
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3575 Views
Shoulder Physiotherapy Activity Recognition 9-Axis Dataset (SPARS9x)
Suggested uses of this dataset include performing supervised classification analysis of physiotherapy exercises, or to perform out-of-distribution detection analysis with unlabeled activities of daily living data.
Description:
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The dataset provides Abilify Oral user reviews and ratings for drug’s satisfaction, effectiveness, and ease of use on different age groups.
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A dataset of the senior high students.
The dataset contains :
1_teacher.csv contains the corresponding information of the teachers;
2_student.csv contains the corresponding information of the students;
3_kaoqin.csv contains the attendance information of the students;
4_kaoqintype.csv contains the type of attendance.
5_chengji.csv contains the grades of the students.
6_exam_type.csv contains the type of examinations.
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736 Views