Peer Reviewed Journal Articles Using SKDH

• 23. Lin et al., “Can Gait Characteristics Be Represented by Physical Activity Measured with Wrist-Worn Accelerometers?,” Sensors, vol. 23, no. 20, Art. no. 20, Jan. 2023, doi: 10.3390/s23208542.

• 23. Lin et al., “SciKit Digital Health Package for Accelerometry-Measured Physical Activity: Comparisons to Existing Solutions and Investigations of Age Effects in Healthy Adults”, Front. Digit. Health, 26 Nov. 2023, doi: 10.3389/fdgth.2023.1321086

• 10. Di et al., “Monitoring Activity and Gait in Children (MAGIC) using digital health technologies,” Pediatr Res, Mar. 2024, doi: 10.1038/s41390-024-03147-x.

• 16. Sheriff et al., “In-Clinic and Natural Gait Observations (I-CAN-GO) an Observational Low-Interventional Master Protocol to Validate Gait and Physical Activity in Adults”, In Preparation

• 14. Camerlingo et al., “Measuring gait parameters from a chest-worn accelerometer in healthy individuals: a validation study”, In Preparation

Journal Articles Using Previous Versions of SKDH algorithms

• 12. Adamowicz et al., “Assessment of Sit-to-Stand Transfers during Daily Life Using an Accelerometer on the Lower Back,” Sensors, vol. 20, no. 22, Art. no. 22, Jan. 2020, doi: 10.3390/s20226618.

• 13. 4. Czech et al., “Age and environment-related differences in gait in healthy adults using wearables,” npj Digital Medicine, vol. 3, no. 1, Art. no. 1, Sep. 2020, doi: 10.1038/s41746-020-00334-y.

• 14. Mahadevan et al., “Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices,” npj Digit. Med., vol. 4, no. 1, pp. 1–10, Mar. 2021, doi: 10.1038/s41746-021-00402-x.