Miniaturized Sensors to Monitor Simulated Lunar Locomotion

作者：Hanson Andrea M; Gilkey Kelly M; Perusek Gail P; Thorndike David A; Kutnick Gilead A; Grodsinsky Carlos M; Rice Andrea J; Cavanagh Peter R^*

来源：Aviation Space and Environmental Medicine, 2011, 82(2): 128-132.

DOI：10.3357/ASEM.2825.2011

• activity recognition
• eZLS
• gait
• reduced gravity
• wireless sensor
• neural network

HANSON AM, GILKEY KM, PERUSEK GP, THORNDIKE DA, KUTNICK GA, GRODSINSKY CM, RICE AJ, CAVANAGH PR. Miniaturized sensors to monitor simulated lunar locomotion. Aviat Space Environ Med 2011; 82:128-32. Introduction: Human activity monitoring is a useful tool in medical monitoring, military applications, athletic coaching, and home health-care. We propose the use of an accelerometer-based system to track crewmember activity during space missions in reduced gravity environments. It is unclear how the partial gravity environment of the Moon or Mars will affect human locomotion. Here we test a novel analogue of lunar gravity in combination with a custom wireless activity tracking system. Methods: A noninvasive wireless accelerometer-based sensor system, the activity tracking device (ATD), was developed. The system has two sensor units; one footwear-mounted and the other waist-mounted near the midlower back. Subjects (N = 161 were recruited to test the system in the enhanced Zero Gravity Locomotion Simulator (eZLS) at NASA Glenn Research Center. Data were used to develop an artificial neural network for activity recognition. Results: The eZLS demonstrated the ability to replicate reduced gravity environments. There was a 98%, agreement between the ATD and force plate-derived stride times during running (9.7 km . h(-1)) at both 1 g and 1/6 g. A neural network was designed and successfully trained to identify lunar walking, running, hopping, and loping from ATD measurements with 100% accuracy. Discussion: The eZLS is a suitable tool for examining locomotor activity at simulated lunar gravity. The accelerometer-based AID system is capable of monitoring human activity and may be suitable for use during remote, long-duration space missions. A neural network has been developed to use data from the ATD to aid in remote activity monitoring.

• 出版日期2011-2