Little is known about the effectiveness of the robot-driven therapeutic devices in preventing osteoporosis from happening during the early stage of stroke.
The nCounters Engineering data logger was used to gather the peak ground reaction force (PGRF) data along with CT imaging of patient tibia – these results were used as input to predict the bone health by developing a computational model based on previous studies. The data logger by its design allowed data to be taken from both the back and the front of the foot. A requirement for this experiment.
Robot Clinical Trials using Data Logger
Experiments using the nCounters Data Logger and treadmill showed the relationship between the vertical PGRF and gait speed correlated well with what the researchers expected.
Data from the Excel program that comes with the data logger showed at what percentage (%) of stance time did the PGRFs occur. This was very helpful for the experiment.
The differences in PGRF to when walking at same speed when attached to a robot, as opposed to on a treadmill was there was not the extra force from heel strike and the toeing off you get when walking on a treadmill.
Note: The robot used here is a static robot which constrains the subjects to exercise in a fixed place. This study determined that a static robot can be used to reduce the risk of bone resorption, and hence prevent development of osteoporosis for motor impaired patients.
Without such a robotic intervention there is a four-fold increase in the risk of osteoporotic fractures within the first post-stroke year.
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Peter designs and builds biofeedback products for gait and movement in the orthopaedic and stroke rehabilitation spaces. These devices are programmed for ease of use with built in help touch screens. In all cases data is transferred wirelessly to ensure patient safety.They can store and display data in real time so as to monitor the patient’s overall progress.