Aging is characterized by progressive functional decline and reduced lifespan; these two parameters are often evaluated independently in experimental studies. In Drosophila melanogaster, lifespan assays and negative geotaxis-based locomotor measurements are commonly used to study aging and neurodegeneration. However, there is a lack of standardized frameworks that quantitatively integrate early motor performance with long-term survival. Here, we describe a reproducible, semi-automated workflow that combines lifespan analysis with objective quantification of motor healthspan in aging flies. The protocol integrates controlled fly rearing conditions, mortality accounting, and video-based negative geotaxis assays using standardized MP4 recordings (minimum 1280 × 720 resolution, 30 frames/s). Locomotor performance is quantified using a custom Python-based pipeline implemented in Python 3.12.1 with OpenCV 4.9.0, NumPy 1.26.4, Pandas 2.2.0, and Matplotlib 3.5.2. The workflow performs frame-by-frame centroid detection and extracts active climbing slope (pixels/s) as a continuous metric of motor function. Survival trajectories are analyzed by calculating the survival fraction and performing trapezoidal numerical integration to obtain the survival area under the curve (AUC). Normalization of early motor performance enables direct comparison between functional decline and overall longevity. The workflow was evaluated by comparing semi-automated climbing slope measurements with conventional manual endpoint scoring in control and amyloid-β-expressing flies, with both methods detecting age-dependent motor decline. Representative datasets demonstrated reproducible lifespan trajectories in Canton S controls and measurable early motor impairment in the neurodegenerative model. This method minimizes observer bias, enhances reproducibility, and remains compatible with low-cost video acquisition systems. The workflow can be readily adapted to genetic models, pharmacological interventions, and neurodegenerative paradigms, providing a scalable platform for integrated aging phenotyping in Drosophila.
