Systems and methods for rehabilitation of limb motion
Systems and methods for rehabilitation of limb motion are described herein. An example system can include a thermal imaging device for imaging a subject or a plurality of sensors for sensing force or pressure exerted by a portion of the subject's body. The system can also include a processor and a memory operably coupled to the processor. The processor can be configured to receive force or pressure data measured by the sensors or image data captured by the thermal imaging device, and calculate a quantitative measure of the subject's limb motion based on the force or pressure data or the image data.
1. A system for rehabilitation of limb motion, comprising:
at least one of a thermal imaging device for imaging a subject or a plurality of sensors for sensing force or pressure exerted by a portion of the subject's body;
a processor; and
a memory operably coupled to the processor, the memory having computer-executable instructions stored thereon that, when executed by the processor, cause the processor to:
receive at least one of force or pressure data measured by the sensors or image data captured by the thermal imaging device, and
calculate a quantitative measure of the subject's limb motion based on the force or pressure data or the image data.
2. The system of claim 1 , wherein the sensors are configured to measure a respective pressure exerted by each of the subject's feet.
3. The system of claim 1 , wherein the sensors are thin-film pressure sensors configured for placement in the subject's footwear.
4. The system of claim 1 , wherein the thermal imaging device captures motion of the subject's lower limbs.
5. The system of claim 1 , wherein the thermal imaging device is configured to transmit the image data over a wireless link, or wherein the sensors are configured to transmit the force or pressure data over a wireless link.
6. The system of claim 1 , wherein the quantitative measure of the subject's limb motion comprises at least one of a height of raising a limb, a motion cycle similarity score, a quality of periodicity of limb trajectory, or a balance capability of the subject.
7. The system of claim 1 , further comprising a display device, wherein the memory has further computer-executable instructions stored thereon that, when executed by the processor, cause the processor to generate an instruction related to the subject's limb motion based on the quantitative measure, and wherein the instruction is graphically displayed on the display device.
8. The system of claim 1 , wherein the memory has further computer-executable instructions stored thereon that, when executed by the processor, cause the processor to:
extract a motion series from the image data, the motion series defining the subject's limb motion in at least one dimension; and
recognize one or more normal motion cycles within the motion series based on a comparison between a peak pattern of the motion series and a peak pattern of a template motion series, wherein the template motion series defines a normal motion cycle.
9. The system of claim 8 , wherein the memory has further computer-executable instructions stored thereon that, when executed by the processor, cause the processor to recognize one or more abnormal motion cycles within the motion series based on the comparison between the peak pattern of the motion series and the peak pattern of the template motion series.
10. The system of claim 8 , wherein calculating a quantitative measure of the subject's limb motion further comprises calculating a motion cycle similarity score between one or more peaks within the motion series and one or more peaks within the template motion series.
11. The system of claim 8 , wherein the peak pattern comprises at least one of an amplitude, order, or speed of peaks.
12. The system of claim 1 , wherein the memory has further computer-executable instructions stored thereon that, when executed by the processor, cause the processor to:
extract a motion series from the image data, the motion series defining the subject's limb motion in at least one dimension; and
transform the motion series into a spatial domain, wherein calculating a quantitative measure of the subject's limb motion further comprises deriving a quality of periodicity of limb trajectory based on the motion series in the spatial domain.
13. The system of claim 12 , wherein transforming the motion series into a spatial domain comprises Time-Delay Embedding (TDE).
14. The system of claim 12 , wherein deriving a quality of periodicity of limb trajectory based on the motion series in the spatial domain further comprises calculating a linear density of a shortest path of an attractor formed by the motion series in the spatial domain.
15. The system of claim 12 , wherein the subject's limb motion comprises a trajectory of at least a portion of the subject's foot.
16. The system of claim 1 , wherein the memory has further computer-executable instructions stored thereon that, when executed by the processor, cause the processor to determine a pressure distribution between the subject's feet, and wherein calculating a quantitative measure of the subject's limb motion further comprises determining a balance capability of the subject based on the pressure distribution between the subject's feet.
17. The system of claim 16 , wherein the pressure distribution between the subject's feet is a plantar pressure distribution.
18. The system of claim 16 , wherein the memory has further computer-executable instructions stored thereon that, when executed by the processor, cause the processor to identify at least one of a weak or disabled limb, an abnormal walking condition, or an imbalance of the subject.