Spatial heterogeneity in the response of the proximal femur to two lower-body resistance exercise regimens.

Understanding the skeletal effects of resistance exercise involves delineating the spatially heterogeneous response of bone to load distributions from different muscle contractions. Bone mineral density (BMD) analyses may obscure these patterns by averaging data from tissues with variable mechanoresponse. To assess the proximal femoral response to resistance exercise, we acquired pretraining and posttraining quantitative computed tomography (QCT) images in 22 subjects (25-55 years, 9 males, 13 females) performing two resistance exercises for 16 weeks. One group (SQDL, n = 7) performed 4 sets each of squats and deadlifts, a second group (ABADD, n = 8) performed 4 sets each of standing hip abductions and adductions, and a third group (COMBO, n = 7) performed two sets each of squat/deadlift and abduction/adduction exercise. Subjects exercised three times weekly, and the load was adjusted each session to maximum effort. We used voxel-based morphometry (VBM) to visualize BMD distributions. Hip strength computations used finite element modeling (FEM) with stance and fall loading conditions. We used QCT analysis for cortical and trabecular BMD, and cortical tissue volume. For muscle size and density, we analyzed the cross-sectional area (CSA) and mean Hounsfield unit (HU) in the hip extensor, flexor, abductor, and adductor muscle groups. Whereas SQDL increased vertebral BMD, femoral neck cortical BMD and volume, and stance hip strength, ABADD increased trochanteric cortical volume. The COMBO group showed no changes in any parameter. VBM showed different effects of ABADD and SQDL exercise, with the former causing focal changes of trochanteric cortical bone, and the latter showing diffuse changes in the femoral neck and head. ABADD exercise increased adductor CSA and HU, whereas SQDL exercise increased the hip extensor CSA and HU. In conclusion, we observed different proximal femoral bone and muscle tissue responses to SQDL and ABADD exercise. This study supports VBM and volumetric QCT (vQCT) to quantify the spatially heterogeneous effects of types of muscle contractions on bone.

Miniaturized sensors to monitor simulated lunar locomotion.

INTRODUCTION: Human activity monitoring is a useful tool in medical monitoring, military applications, athletic coaching, and home healthcare. 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 Moorn 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=16) 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 x 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 ATD 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.