Daily and Sports Activities Dataset & Task

docs/api/datasets.rst

@@ -243,5 +243,6 @@ Available Datasets
     datasets/pyhealth.datasets.ClinVarDataset
     datasets/pyhealth.datasets.COSMICDataset
     datasets/pyhealth.datasets.TCGAPRADDataset
+    datasets/pyhealth.datasets.DSADataset
     datasets/pyhealth.datasets.splitter
     datasets/pyhealth.datasets.utils

docs/api/datasets/pyhealth.datasets.DSADataset.rst

@@ -0,0 +1,10 @@
+pyhealth.datasets.DSADataset
+===============================
+
+The Daily and Sports Activities (DSA) dataset contains motion sensor data of 
+daily and sports activities. For more information see `Daily and Sports Activities <https://archive.ics.uci.edu/dataset/256/daily+and+sports+activities>`_. This dataset was contributed as part of the Prostate-VarBench benchmarking work (`arXiv:2511.09576 <https://arxiv.org/abs/2511.09576>`_).
+
+.. autoclass:: pyhealth.datasets.DSADataset
+    :members:
+    :undoc-members:
+    :show-inheritance:

docs/api/tasks.rst

@@ -229,3 +229,4 @@ Available Tasks
     Mutation Pathogenicity (COSMIC) <tasks/pyhealth.tasks.MutationPathogenicityPrediction>
     Cancer Survival Prediction (TCGA) <tasks/pyhealth.tasks.CancerSurvivalPrediction>
     Cancer Mutation Burden (TCGA) <tasks/pyhealth.tasks.CancerMutationBurden>
+    Activity Classification (DSA) <tasks/pyhealth.tasks.ActivityClassification>

docs/api/tasks/pyhealth.tasks.ActivityClassification.rst

@@ -0,0 +1,7 @@
+pyhealth.tasks.ActivityClassification
+===================================
+
+.. autoclass:: pyhealth.tasks.ActivityClassification
+    :members:
+    :undoc-members:
+    :show-inheritance:

examples/dsa_activity_classification.py

@@ -0,0 +1,49 @@
+# -*- coding: utf-8 -*-
+"""dsa_activity_classification.ipynb
+
+# Activity Classification Using DSA Dataset
+
+# Install PyHealth
+
+You might need to restart kernel after running this section.
+"""
+
+!git clone https://github.com/ranyou/PyHealth.git
+!cd PyHealth && pip install -e .
+
+"""# Load Dataset"""
+
+from pyhealth.datasets import DSADataset
+
+dataset = DSADataset(download=True, root="./daily-and-sports-activities")
+dataset.stats()
+
+"""# Define Task"""
+
+samples = dataset.set_task()
+
+from pyhealth.datasets import get_dataloader, split_by_sample
+
+train_dataset, val_dataset, test_dataset = split_by_sample(samples, [0.7, 0.1, 0.2])
+
+train_loader = get_dataloader(train_dataset, batch_size=16, shuffle=True)
+val_loader = get_dataloader(val_dataset, batch_size=16, shuffle=False)
+test_loader = get_dataloader(test_dataset, batch_size=16, shuffle=False)
+
+"""# Define Model"""
+
+from pyhealth.models import RNN
+
+model = RNN(samples)
+
+"""# Train Model"""
+
+from pyhealth.trainer import Trainer
+
+trainer = Trainer(model=model, metrics=["accuracy"])
+trainer.train(train_dataloader=train_loader, val_dataloader=val_loader, epochs=1)
+
+"""# Evaluate Model"""
+
+trainer.evaluate(test_loader)
+

pyhealth/datasets/__init__.py

@@ -53,6 +53,7 @@ def __init__(self, *args, **kwargs):
 from .cosmic import COSMICDataset
 from .covid19_cxr import COVID19CXRDataset
 from .dreamt import DREAMTDataset
+from .dsa import DSADataset
 from .ehrshot import EHRShotDataset
 from .eicu import eICUDataset
 from .isruc import ISRUCDataset

pyhealth/datasets/configs/dsa.yaml

@@ -0,0 +1,136 @@
+version: "1.0"
+tables:
+  activities:
+    file_path: "dsa-pyhealth.csv"
+    patient_id: "patient"
+    timestamp: null
+    attributes:
+    - "activity"
+    - "patient"
+    - "segment"
+    - "sensor"
+    - "0"
+    - "1"
+    - "2"
+    - "3"
+    - "4"
+    - "5"
+    - "6"
+    - "7"
+    - "8"
+    - "9"
+    - "10"
+    - "11"
+    - "12"
+    - "13"
+    - "14"
+    - "15"
+    - "16"
+    - "17"
+    - "18"
+    - "19"
+    - "20"
+    - "21"
+    - "22"
+    - "23"
+    - "24"
+    - "25"
+    - "26"
+    - "27"
+    - "28"
+    - "29"
+    - "30"
+    - "31"
+    - "32"
+    - "33"
+    - "34"
+    - "35"
+    - "36"
+    - "37"
+    - "38"
+    - "39"
+    - "40"
+    - "41"
+    - "42"
+    - "43"
+    - "44"
+    - "45"
+    - "46"
+    - "47"
+    - "48"
+    - "49"
+    - "50"
+    - "51"
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+    - "124"