Kinetic Sensing, Signal Generation, Feature Extraction, And Pattern Recognition For Control Of Autonomous Wearable Leg Devices
20190307583 ยท 2019-10-10
Inventors
- Hugh M. Herr (Somerville, MA)
- Roman Stolyarov (Bristol, RI, US)
- Luke M. Mooney (Westford, MA, US)
- Cameron Taylor (Cambridge, MA, US)
- Matthew Carney (Somerville, MA, US)
Cpc classification
A61F2002/763
HUMAN NECESSITIES
A61F2002/7635
HUMAN NECESSITIES
A61F2002/7685
HUMAN NECESSITIES
A61F5/0102
HUMAN NECESSITIES
B25J9/0006
PERFORMING OPERATIONS; TRANSPORTING
A61H3/00
HUMAN NECESSITIES
A61B5/7275
HUMAN NECESSITIES
International classification
A61B5/00
HUMAN NECESSITIES
A61B5/11
HUMAN NECESSITIES
B25J9/00
PERFORMING OPERATIONS; TRANSPORTING
A61F5/01
HUMAN NECESSITIES
Abstract
An autonomous wearable leg device employs an array of sensors embedded along a support area, whereby a controller can generate a controlling command and send a controlling command to a prosthetic, orthotic, exoskeletal or wearable component to thereby control the prosthetic, orthotic, exoskeletal or wearable component. A method for controlling autonomous wearable device collects kinetic signals from an array of sensors embedded in a prosthetic, orthotic or exoskeletal component, wherein all values are extracted from at least one feature of the collected kinetic signals, which are applied to a controller that generates a controlling command that is sent to the prosthetic, orthotic exoskeletal component to thereby control the prosthetic, orthotic or exoskeletal component during a portion of a gait cycle.
Claims
1. A method for controlling an autonomous wearable leg device, comprising the steps of: a) collecting signals from one or more kinetic sensors embedded in a component of the autonomous wearable leg device b) employing features extracted from these signals to predict or estimate gait events, gait activities, or terrains in real time c) using predictions or estimates of gait events, gait activities, or terrains to send control commands to the autonomous wearable leg device in real time
2. The method of claim 1, where the autonomous wearable leg device is an autonomous transfemoral or transtibial prosthesis, exoskeleton, or orthotic device.
3. The method of claim 1, wherein one or multiple kinetic sensors are a load cell embedded within the prosthetic thigh or shank of a transfemoral or transtibial prosthesis.
4. The method of claim 1, wherein one or multiple kinetic sensors are embedded within a component of the autonomous wearable leg device support area.
5. The method of claim 4, wherein components of the autonomous wearable leg device support area include the prosthetic foot or foot cover, sock, insole, or shoe.
6. The method of claim 1, wherein gait events include establishment or breaking of physical contact between the foot and the ground, establishment of a foot-flat position, heel strike, toe strike, stopping and starting gait, and changing of gait speed.
7. The method of claim 1, wherein gait activities include walking, shuffling, jogging, or running in an anterior, posterior, or lateral direction, jumping, standing on the toes, or squatting.
8. The method of claim 1, wherein terrains include ascending or descending stairs, inclines, declines, obstacles, soft surfaces, and uneven surfaces.
9. The method of claim 1, further including the step of employing the kinetic signals to provide feedback to the user of the autonomous wearable leg device in real time.
10. The method of claim 9, wherein the feedback is in the form of at least one of mechanical stimuli and electrical stimuli.
11. The method of claim 10, wherein the feedback is in the form of mechanical stimuli.
12. The method of claim 11, wherein the mechanical stimuli include at least one member from the group consisting of: vibration; application of pressure to skin; pinching of skin; application of strain to skin; and variation of surface temperature applied to skin.
13. The method of claim 10, wherein the feedback is in the form of electrical stimuli.
14. The method of claim 13, wherein the electrical stimuli include at least one member selected from the group consisting of electrical stimulation of at least one of a muscle and a nerve.
15. A method for controlling an autonomous wearable leg device, comprising the steps of: a) detecting or characterizing obstacles or terrain changes in real time using non-contact sensors integrated into a foot covering b) using the detection or characterization of obstacles or terrains to modulate a control algorithm of the autonomous wearable leg device in real time
16. The method of claim 15, wherein the autonomous wearable leg device is a powered prosthesis, orthosis, or exoskeleton.
17. The method of claim 15, wherein the foot covering is a prosthetic cosmesis or a shoe.
18. The method of claim 15, wherein the non-contact sensors include one or multiple cameras, distance-measuring sensors, or laser scanners.
19. The method of claim 15, wherein one non-contact sensor is positioned in a forward orientation at a toe area of a shoe, whereby it is used to predict that the user will ascend stairs or clear an obstacle.
20. The method of claim 15, wherein one non-contact sensor is positioned in a downward orientation at the toe area of a shoe, whereby it is used to predict that the user will descent stairs when they position a lower extremity at the edge of a stair.
21. The method of claim 15, wherein one non-contact sensor is positioned in a backward orientation at the back area of a shoe, whereby it is used to detect stair descent.
22. The method of claim 15, wherein the control algorithm is used to actuate a prosthetic joint with a torque or position profile consistent with established biological norms for a predicted terrain.
23. An autonomous wearable leg device, comprising: a) an ankle frame; b) a pair of actuators, each actuator being mounted on the frame and connectable to a power source, and control signal, wherein the actuators are independently controllable; c) an eccentric crank-arm linkage connecting the actuator to the foot interface; d) a foot interface connected to the actuators, whereby actuation of either of the actuators transmits force to the foot interface; and e) at least one hinge at the frame linking the ankle frame to the foot interface, whereby synchronous movement of the actuators causes plantarflexion or dorsiflexion of the foot interface component, and differential movement of the linkages causes eversion or inversion of the foot interface.
24. The autonomous device of claim 23, wherein the hinge includes a ball and socket assembly.
25. The autonomous device of claim 23, wherein the hinge includes a gimbal assembly.
26. The autonomous device of claim 24, wherein the gimbal assembly defines two axes of rotation, whereby one of the two axes defines an axis of rotation for dorsiflexion and plantarflexion, and the other of the two axes defines an axis of rotation for eversion and inversion of the first foot interface.
27. The autonomous device of claim 25, wherein the axes of rotation intersect.
28. The autonomous device of claim 26, wherein the axes of rotation intersect orthogonally.
29. The autonomous device of claim 26, wherein the axes of rotation intersect at an angle that is not orthogonal.
30. The autonomous device of claim 25, wherein the axes of rotation do not intersect.
31. The autonomous device of claim 29, wherein the axes of rotation are oriented orthogonally.
32. The autonomous device of claim 29, wherein the axes of rotation are oriented askew.
33. The autonomous device of claim 23, wherein the hinges include an ankle joint and subtalar joint linked to the ankle joint, wherein the ankle joint includes one degree of freedom, and the subtalar joint includes the other degree of freedom.
34. The autonomous device of claim 23, wherein the actuators are mirrored across a sagittal plane of the prosthesis.
35. The autonomous device of claim 23, wherein the actuators are each connected to the foot frame by way of an eccentric crank-arm linkage.
36. The autonomous device of claim 23, wherein the eccentric crank-arm linkage assembly of each actuator includes a gear reduction component having a serially-connected multi-stage timing belt drive-train and an output timing pulley linking the timing belt drive train with the respective linkage.
37. The autonomous device of claim 32, further including a foot component connected to the foot interface.
38. The autonomous device of claim 33, wherein the motors are split phase sector motors.
39. The autonomous device of claim 34, wherein the foot component includes at least one powered metatarsophalangeal joint.
40. The autonomous device of claim 23, further including a knee component connected to the ankle frame, having a single degree of freedom.
41. The autonomous device of claim 38, wherein the knee component includes a knee joint and a powered knee actuation system linked to the knee joint, wherein the knee joint has the degree of freedom of the knee component.
42. The autonomous device of claim 39, wherein the powered knee actuation system includes a clutched series static actuator.
43. The autonomous device of claim 40, wherein ankle component includes an ankle joint and a subtalar joint linked to the ankle joint, wherein the ankle joint includes one degree of freedom, and the subtalar joint includes the other degree of freedom of the ankle component.
44. The autonomous device of claim 41, wherein the foot component includes a metatarsophalangeal joint having the degree of freedom of the foot component.
45. The autonomous device of claim 42, wherein the knee component further includes a series elastic actuator.
46. The autonomous device of claim 43, wherein the series elastic actuator is a clutchable series elastic actuator.
47. A foot device that functions as one or more powered metatarsophalangeal joints, comprising: a) a mounting plate that is a foot frame; b) an actuator mounted on the foot frame and connectable to a power source, and control signal, wherein the actuator is independently controllable; and c) a hinge linked to the foot frame, and d) a toe component that is linked to the actuator, whereby the actuator causes the toe component to move relative to the hinge joint, thereby functioning as a powered metatarsophalangeal joint of the foot.
48. The foot device of claim 47, wherein the hinge is a flexural hinge.
49. The foot device of claim 47, wherein the hinge is a revolute hinge.
50. The foot device of claim 47, further including a parallel elastic element with one end fixed to the foot frame and the other end free to apply force to the toe component about the hinge, whereby elastic force of the elastic element moves the hinge to a minimum energy position.
51. The foot device of claim 47, further including an appendage component assembly having parallel elastic members.
52. The foot device of claim 51, wherein the parallel elastic members are one or a plurality of cantilever beams fixed to the foot frame and apply a normal force a distance from the hinge toward the toe component.
53. The foot device of claim 51, further including rigid spring clamps, wherein the parallel elastic members are fixed to the foot frame by being clamped between the rigid spring clamps and the foot frame.
54. The foot device of claim 51, wherein the actuator includes a motor, a capstan, a tensile strand.
55. The foot device of claim 54 wherein the stiffness of the hinge is modulated by the change in length of the tensile strand affecting the preload of the parallel elastic members.
56. The foot device of claim 47, wherein the hinge includes a parallel elastic element and at least one of a crank arm, a push-rod assembly, and an actuator that provides output torque regulation by modulating the motion of the output appendage about the joint and thereby modulating the loading of the parallel elastic element.
57. A method for controlling an autonomous wearable device, comprising the steps of: a) collecting kinetic signals from an array of sensors embedded in a prosthetic, orthotic or exoskeletal component of the autonomous wearable device worn by a subject during a portion of a gait cycle; b) extracting raw values of at least one feature from the collected kinetic signals; c) applying the raw values of the feature to a controller; d) generating a controlling command with the controller; and e) sending the controlling command to the prosthetic, orthotic or exoskeletal component to thereby control the prosthetic, orthotic or exoskeletal component during the portion of the gait cycle.
58. The method of claim 57, further including classifying the raw values according to a classification algorithm or normalizing the raw values before being applying the raw values to the controller.
59. The method of claim 58, wherein the normalization is by at least one member of the group consisting of: feature mean and standard deviation; and feature extreme and range.
60. The method of claim 57, further including the step of compounding the at least one feature.
61. The method of claim 60, wherein the raw values of a plurality of features are extracted.
62. The method of claim 61, wherein the plurality of features are compounded to produce a secondary feature.
63. The method of claim 58 wherein the at least one feature includes at least one member of the group consisting of: a statistical feature; a time domain feature; a frequency domain feature; and combinations thereof.
64. The method of claim 63, wherein the at least one feature includes a statistical feature.
65. The method of claim 64, wherein the statistical feature includes at least one member of the group consisting of: mean; maximum; minimum; range; mean absolute deviation; variance; standard deviation; and sample size.
66. The method of claim 65, wherein the statistical feature is extracted from the kinetic signals generated during a stance phase of the gait cycle.
67. The method of claim 66, further including the step of detecting the kinetic signals by thresholding an estimated ground reaction force.
68. The method of claim 63, wherein the at least one feature includes a time domain feature.
69. The method of claim 68, wherein the at least one time domain feature is employed in an ARIMA model included in a classification algorithm.
70. The method of claim 69, wherein the at least one time domain feature is selected from the group consisting of: minimum and maximum values calculated from at least one of a beginning and end of a signal collection period; a difference between a combination of the beginning and end of the signal collection period; a number of zero or mean crossings; cross correlations between signals; signal autocorrelations; parameters or orders of autoregressive, integrated, and moving average parts; and combinations thereof.
71. The method of claim 70, wherein the at least one time domain feature is normalized by a length of a stance period during the gait cycle.
72. The method of claim 63, wherein the at least one feature includes a frequency domain feature.
73. The method of claim 63, further including classifying the raw values according to a classification algorithm.
74. The method of claim 72, wherein the at least one frequency domain feature includes: frequencies of k peaks in amplitude in a discrete Fourier transform (DFT) of the collected kinetic signals; kth quartiles of the DFT; and total signal power.
75. The method of claim 57, wherein control of the autonomous wearable device further includes: the step of triggering at least one transition between two members selected from the group consisting of: walking; jogging; running; standing; and sitting.
76. The method of claim 75, wherein the at least one transition employs only the kinetic signals.
77. The method of claim 76, wherein the triggering includes thresholding a vertical ground reaction force.
78. The method of claim 77, wherein the triggering step includes distinguishing at least one member of the group consisting of: walking; jogging; running; and between combinations thereof.
79. The method of claim 78, wherein the triggering step includes distinguishing between at least two members of the group consisting of: walking; running; and jogging.
80. The method of claim 79, wherein the step of distinguishing between the at least two members of the group consisting of: running, walking, and jogging, includes determining the frequency or amplitude of ground reaction force fluctuation.
81. The method of claim 80, wherein the step of distinguishing between the at least two members of the group consisting of: running, walking, or jogging, includes anticipating terrain and transitioning in real time.
82. The method of claim 81, wherein the step of anticipating terrain includes the step of pattern recognition among the collected kinetic signals during a phase of the gait angle.
83. The method of claim 82, wherein the pattern recognition step includes the at least one kinetic signal in at least one member selected from the group consisting of: a Nave Bayesian classification; a decision tree classification; a discriminant analysis classifier; a referral network classifier; and a logistic regression classifier.
84. The method of claim 57, wherein the array of kinetic sensors is located at at least a portion of a sole of the prosthetic, orthotic or exoskeletal component.
85. The method of claim 84, wherein the array of kinetic sensors is located at a portion of the sole of the prosthetic, orthotic or exoskeletal component.
86. The method of claim 85, wherein the portion of the sole is at least one member of the group consisting of a heel, an arch, a ball region, and a center of pressure of the prosthetic, orthotic or exoskeletal component.
87. The method of claim 84, wherein the array of kinetic sensors is embedded across essentially the entire sole of the prosthetic, orthotic or exoskeletal component.
88. The method of claim 84, further including the step of employing at least one biomimetic control profile to control at least one control variable of the prosthetic, orthotic, or exoskeletal component in response to pattern recognition produced by the pattern recognition step.
89. The method of claim 88, wherein a plurality of biomimetic control profiles are employed.
90. The method of claim 89, wherein the biomimetic control profiles employed correspond to at least one state of at least one task type.
91. The method of claim 90, wherein the task type includes at least one member selected from the group consisting of: walking on a level or sloped terrain; walking upstairs; walking downstairs; jogging on level or sloped terrain; jogging upstairs; jogging downstairs; running on level or slopped terrain; running upstairs; and running downstairs.
92. The method of claim 85, wherein the at least one control variable of the at least one biomimetic control profile includes at least one member selected from the group consisting of: center pressure; radial power; linear power; force; position; velocity; and work.
93. The method of claim 92, further including the step of modulating at least one control variable in accordance with at least one of a threshold and a calculation employing at least one state variable of at least one task type.
94. The method of claim 93, wherein the at least one state variable includes at least one member selected from the group consisting of: at least a portion of the collected kinetic signals; joint kinetics; ambulatory speed; user intact; variation of ground surface slope, altitude; material; added mechanical loads on the user; and user posture.
95. The method of claim 57, further including employing the kinetic signals to generate a data base.
96. The method of claim 95, further including the kinetic signals of the data base to thereby produce diagnostic information from at least one member of the group consisting of: diagnostic statistics; step counts; information about power, information about force output; time spent; electrical work done; and metabolic work done.
97. The method of claim 96, wherein the diagnostic information is directed to at least one member selected from the group consisting of modes, tasks and status.
98. The method of claim 57, further including the step of employing the kinetic signals to provide feedback to the subject.
99. The method of claim 98, wherein the feedback is in the form of at least one of mechanical stimuli and electrical stimuli.
100. The method of claim 99, wherein the feedback is in the form of mechanical stimuli.
101. The method of claim 100, wherein the mechanical stimuli include at least one member from the group consisting of: vibration; application of pressure to skin; pinching of skin; application of strain to skin; and variation of surface temperature applied to skin.
102. The method of claim 99, wherein the feedback is in the form of electrical stimuli.
103. The method of claim 102, wherein the electrical stimuli include at least one member selected from the group consisting of electrical stimulation of at least one of a muscle and a nerve.
104. A method for controlling an autonomous wearable leg device, comprising the steps of: a) using non-contact sensors integrated into a foot covering to detect or characterize obstacles or terrain changes in real time; and b) using the detection or characterization of obstacles or terrains to modulate a control algorithm of the autonomous wearable leg device in real time
105. The method of claim 104, wherein the autonomous wearable leg device is a powered prosthesis, orthosis, or exoskeleton.
106. The method of claim 105, wherein the foot covering is a prosthetic cosmesis or a shoe.
107. The method of claim 106, wherein the non-contact sensors include one or multiple cameras, distance-measuring sensors, or laser scanners.
108. The method of claim 104, wherein one non-contact sensor is positioned in a forward orientation at a toe area of a shoe, whereby it is used to predict that the user will ascend stairs or clear an obstacle.
109. The method of claim 105, wherein one non-contact sensor is positioned in a downward orientation at the toe area of a shoe, whereby it is used to predict that the user will descent stairs when they position a lower extremity at the edge of a stair.
110. The method of claim 105, wherein one non-contact sensor is positioned in a backward orientation at the back area of a shoe, whereby it is used to detect stair descent.
111. The method of claim 105, wherein the control algorithm is used to actuate a prosthetic joint with a torque or position profile consistent with established biological norms for a predicted terrain.
112. A autonomous wearable leg device for integrated, real time, and kinetic sensing, comprising: a) a prosthetic, orthotic or exoskeletal component that includes a support area; b) an array of sensors embedded along the support area; and c) a controller in communication with the array, whereby the sensors of the array can collectively sense and transmit spatially-dependent pressure signals to the controller, and whereby the controller can generate a controlling command and send the controlling command to the prosthetic, orthotic or exoskeletal component, and thereby control the prosthetic, orthotic, or exoskeletal component.
113. The device of claim 112, wherein the component includes at least one member of the group consisting of: a prosthetic foot; a foot cover; a prosthetic socket; a sole of a shoe; a sock; a six-axis load cell; a transtibial load cell; and a transfemoral load cell.
114. The device of claim 112, wherein the sensors are arrayed to estimate, in combination with the controller, at least one of a center of pressure and strain.
115. The device of claim 112, wherein the sensors are arrayed in a transverse plane to a longitudinal axis of a subject wearing the device.
116. The device of claim 112, wherein the sensors are arrayed to estimate, in combination with the controller, a ground reaction force on the array.
117. The device of claim 112, wherein the component is a transverse foot section and the sensors are arrayed to estimate, in combination with the controller, a ground reaction force on the transverse foot section.
118. The device of claim 117, wherein the transverse foot section is at least one member of the group consisting of a ball, a heel, an arch, and a combination thereof.
119. An autonomous prosthetic, orthotic, or exoskeletal device, comprising: a) an ankle frame; b) a pair of actuators, each actuator being mounted on the frame and connectable to a power source, and control signal, wherein the actuators are independently controllable; c) a foot interface connected to the actuators, whereby actuation of either of the actuators transmits force to the foot interface; and d) at least one hinge at the frame linking the ankle frame to the foot interface, whereby synchronous movement of the actuators causes plantarflexion or dorsiflexion of the foot interface component, and differential movement of the linkages causes eversion or inversion of the foot interface.
120. The autonomous device of claim 119, wherein the hinge includes a gimbal assembly.
121. The autonomous device of claim 120, wherein the gimbal assembly defines two axes of rotation, whereby one of the two axes defines an axis of rotation for dorsiflexion and plantarflexion, and the other of the two axes defines an axis of rotation for eversion and inversion of the first foot interface.
122. The autonomous device of claim 121, wherein the axes of rotation intersect.
123. The autonomous device of claim 122, wherein the axes of rotation intersect orthogonally.
124. The autonomous device of claim 122, wherein the axes of rotation intersect at an angle that is not orthogonal.
125. The autonomous device of claim 121, wherein the axes of rotation do not intersect.
126. The autonomous device of claim 125, wherein the axes of rotation are oriented orthogonally.
127. The autonomous device of claim 125, wherein the axes of rotation are oriented askew.
128. The autonomous device of claim 119, wherein the at least one hinge includes an ankle joint and subtalar joint linked to the ankle joint, wherein the ankle joint includes one degree of freedom, and the subtalar joint includes the other degree of freedom.
129. The autonomous device of claim 119, wherein the actuators are mirrored across a sagittal plane of the prosthesis.
130. The autonomous device of claim 119, wherein each actuator includes a gear reduction component having a serially-connected multi-stage timing belt drive-train and an output timing pulley linking the timing belt drive train with the respective linkage.
131. The autonomous device of claim 128, further including a foot component connected to the foot interface.
132. The autonomous device of claim 119, wherein the actuators are split-phase sector motors.
133. The autonomous device of claim 132, wherein the foot component includes a powered metatarsophalangeal joint.
134. The autonomous device of claim 119, further including a knee component connected to the ankle frame, having a single degree of freedom.
135. The autonomous device of claim 134, wherein the knee component includes a knee joint and a powered knee actuation system linked to the knee joint, wherein the knee joint has the degree of freedom of the knee component.
136. The autonomous device of claim 135, wherein the powered knee actuation system includes a clutched series static actuator.
137. The autonomous device of claim 136, wherein ankle component includes an ankle joint and a subtalar joint linked to the ankle joint, wherein the ankle joint includes one degree of freedom, and the subtalar joint includes the other degree of freedom of the ankle component.
138. The autonomous device of claim 137, wherein the foot component includes a metatarsophalangeal joint having the degree of freedom of the foot component.
139. The autonomous device of claim 138, wherein the knee component further includes a series elastic actuator.
140. The autonomous device of claim 139, wherein the series elastic actuator is a clutchable series elastic actuator.
141. A prosthetic foot that functions as a powered metatarsophalangeal joint, comprising: a) a mounting plate that is a foot frame; b) an actuator mounted on the foot frame and connectable to a power source, and control signal, wherein the actuator is independently controllable; and c) a hinge linked to the foot frame, and d) a toe component that is linked to the actuator, whereby the actuator causes the toe component to move relative to the hinge joint, thereby functioning as a powered metatarsophalangeal joint of the foot.
142. The prosthetic foot of claim 141, wherein the hinge is a flexural hinge.
143. The prosthetic foot of claim 141, wherein the hinge is a revolute hinge.
144. The prosthetic foot of claim 141, further including a parallel elastic element with one end fixed to the foot frame and the other end free to apply force to the toe component about the hinge, whereby elastic force of the elastic element moves the hinge to a minimum energy position.
145. The prosthetic foot of claim 141, further including a foot component assembly at the parallel elastic element.
146. The prosthetic foot of claim 145, wherein the parallel elastic element includes one or a plurality of cantilever beams fixed to the foot frame and apply a normal force a distance from the hinge toward the toe component.
147. The prosthetic foot of claim 145, further including rigid spring clamps, wherein the parallel elastic members are fixed to the foot frame by being clamped between the rigid spring clamps and the foot frame.
148. The prosthetic foot of claim 141, wherein the actuator includes a motor, a capstan, a tensile strand.
149. The prosthetic foot of claim 141, wherein the stiffness of the hinge is modulated by the change in length of the tensile strand affecting the preload of the parallel elastic members.
150. The prosthetic foot of claim 141, wherein the hinge includes a parallel elastic element and at least one of a crank arm, a push-rod assembly, and an actuator at the hinge joint that provides output torque regulation by modulating the loading of the parallel elastic element.
151. An autonomous prosthesis, comprising: a) an actuated knee component with a single actuated degree of freedom; b) an ankle component with two actuated degrees of freedom and linked to the actuated knee component; and c) a foot component with a single actuated degree of freedom and linked to the ankle component.
152. An autonomous prosthesis, comprising: a) an actuated knee component with a single actuated degree of freedom; b) an ankle component with two actuated degrees of freedom and linked to the actuated knee component; and c) a passive foot component.
153. An autonomous prosthesis, comprising: a) a passive knee component; b) an ankle component with two actuated degrees of freedom and linked to the passive knee component; and c) a foot component with a single actuated degree of freedom and linked to the ankle component.
154. An autonomous prosthesis, comprising: a) a passive knee component; b) an ankle component with two actuated degrees of freedom and linked to the passive knee component; and c) a passive foot component linked to the ankle component.
155. An autonomous prosthesis, comprising: a) an ankle component with two actuated degrees of freedom; and b) a foot component with a single actuated degree of freedom and linked to the ankle component.
156. An autonomous prosthesis, comprising: a) an ankle component with two actuated degrees of freedom; and b) a passive foot component linked to the ankle component.
157. A prosthetic device that functions as a powered metatarsophalangeal joint, comprising: a) a mounting plate that is a frame; b) an actuator mounted on the frame and connectable to a power source, and a control signal, wherein the actuator is independently controllable; c) a hinge linked to the frame; and d) an appendage that is linked to the actuator, whereby the actuator causes the appendage to move relative to the hinge joint.
158. The prosthetic device of claim 157, wherein the hinge is a flexural hinge.
159. The prosthetic device of claim 157, wherein the hinge is a revolute hinge.
160. The prosthetic device of claim 157, further including a parallel elastic element with one end fixed to the frame and the other end free to apply force to the appendage about the hinge, whereby elastic force of the elastic element moves the hinge to a minimum energy position.
161. The prosthetic device of claim 157, further including an appendage component assembly having parallel elastic members.
162. The prosthetic device of claim 157, wherein the parallel elastic members are one or a plurality of cantilever beams fixed to the foot frame and apply a normal force a distance from the hinge toward the appendage.
163. The prosthetic device of claim 162, further including rigid spring clamps, wherein the parallel elastic members are fixed to the frame by being clamped between the rigid spring clamps and the frame.
164. The prosthetic device of claim 157, wherein the actuator includes a motor, a capstan, a tensile strand.
165. The prosthetic device of claim 164, wherein the stiffness of the hinge is modulated by the change in length of the tensile strand affecting the preload of the parallel elastic members.
166. The prosthetic device of claim 157, wherein the hinge includes a parallel elastic element and at least one of a crank arm, a push-rod assembly, and an actuator at the hinge joint that provides output torque regulation by modulating the loading of the parallel elastic element.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
[0025] The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.
[0026] The foregoing will be apparent from the following more particular description of example embodiments, as illustrated in the accompanying drawings in which like reference characters refer to the same parts throughout the different views. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating embodiments.
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DETAILED DESCRIPTION OF THE INVENTION
[0048] The inventions described here are directed toward both the control methods and mechanical design of autonomous wearable leg devices (AWLDs) including autonomous transtibial or transfemoral prostheses, exoskeletons, and orthotics.
Control Methods
[0049] These inventions include methods of actuating AWLDs by modulating force or torque, power, position, velocity, work, or other control variables or provide feedback to the user in the form of mechanical or electrical stimuli. The methods of the invention are performed in real time and employ integrated, autonomous sensing, microprocessing, and actuation systems.
[0050] In one embodiment, the invention is a method for controlling an AWLD that incorporates integrated, real-time, kinetic sensing. Kinetic sensors are embedded either on an area for ground support belonging to the AWLD or as one or a plurality of load cells within a prosthetic thigh or shank. A controller is in communication with the sensors, whereby the sensors can collectively sense and transmit spatially-dependent pressure signals or localized forces and moments to the controller, and whereby the controller can generate a controlling command and send the controlling command to AWLD, and thereby control the AWLD.
[0051] In one embodiment, the controller of the AWLD uses the spatially varying pressure signals to estimate ground reaction force (GRF) and center of pressure (COP), and extracts features on these signals within the time window when the support area is in the ground, and inputs these features into a machine learning classifier to predict gait activity, gait event, or terrain of the next step. In this embodiment, the vertical component F.sub.Z of the GRF is estimated as:
[0052] where p.sub.i is the strain at each sensor i and N is then total number of sensels. Furthermore, COP components C.sub.x and C.sub.y can be estimated as:
where x.sub.i and y.sub.i are the positions of each sensor i. Additionally, signals from individual sensors can also be used as input into the controller, whether for actuation in a particular gait state or for detecting and triggering state, task, or mode transitions.
[0053] In the case of a transtibial load cell within a prosthesis, a static model can be used to estimate the GRF vector and location of the COP using three-dimensional moments and forces measured by such a load cell. The estimation contemplates only single stance support and the coordinate system employed for the model is Cartesian. The sign convention for the ground reaction force is positive upward and forward. The reference frames, shown in
[0054] Here the left superscripts represent the reference frame and the right subscripts represent the coordinate direction. The values employed are defined in the following way: .sup.SM.sub.YS, .sup.SF.sub.YS are the moment and force, respectively, around the Y.sub.S axis of frame {S}; .sup.SM.sub.XS, .sup.S F.sub.XS are the moment and force, respectively, around the X.sub.S axis of frame {S}; .sup.SF.sub.ZS is the force in the Z.sub.S direction of frame {S}; .sup.rP.sub.ZS is the distance in Z.sub.S to the COP. For an active prosthesis system this value can be computed as Z.sub.0 cos where Z.sub.0 is the load cell height at zero degrees of ankle flexion and is the shank angle in {G}. This assumes only rotation in the sagittal plane with no adduction or abduction in the joint. Assuming negligible inversion-eversion of the foot-ankle joint system, we can assume that the rotation matrix that relates frames {S} relative to {P} can be represented by this single sagittal angle . Given the COP location, the forces that interact with the ground, relative to the COP frame {P}, can then be expressed as:
.sup.PF.sub.X.sub.
.sup.PF.sub.Y.sub.
.sup.PF.sub.Z.sub.
[0055] In the case of a transfemoral load cell, estimation of COP and GRF can be performed using knowledge of knee state and spatial transformations similar to those used for the transtibial load cell.
[0056] In another embodiment, a machine learning classifier can be used on the kinetic signals to predict upcoming gait events or terrains based on features extracted from these signals in real time. The classifier could include a heuristic method, a Naive Bayesian classifier; a decision tree classifier; a linear or quadratic discriminant classifier; a neural network classifier; and a logistic regression classifier.
[0057] In an embodiment of the invention, a method includes application of kinetic sensing and control to obtain biomimetic control strategies for AWLDs to define a hierarchical control architecture. One level of such a hierarchy is mode, which includes such general activities as walking, running, sitting, or standing. Another level is task, the categories of which vary depending on activity. For example, walking tasks include walking on different terrains such as flat ground, stairs, or inclines. Finally, each task can be composed of a next hierarchical level, namely sequential states which are, typically, periodic. For example, walking on flat ground can be divided into swing phase, controlled plantarflexion, controlled dorsiflexion, and powered plantarflexion at the end of stance. Various modes, tasks, and states along with relevant transitions are visualized in
[0058] In one specific version of this device, an array of kinetic sensors can be embedded along the support area of a standard prosthetic foot cover and used to transmit spatially dependent pressure signals to the prosthesis controller. An example of such a configuration is exhibited in
[0059] Alternatively, an array of such sensors can be embedded within the support area of the prosthetic foot itself, as illustrated in
[0060] In yet another embodiment (not shown), an array of sensors is embedded within a transtibial or transfemoral prosthetic socket, or embedded within the sole of a shoe, or embedded within a sock.
[0061] In still another embodiment, the invention includes real-time provision of mechanical or electrical feedback to the user of an AWLD. Kinetic state variables, as described herein can be employed to provide feedback to the AWLD user in the form of mechanical or electrical stimuli. Mechanical stimuli can include vibration, application of normal pressure to the skin, skin pinching or strain application, or skin surface temperature variation. Electrical stimuli include electrical stimulation of muscles or nerves.
[0062] In another embodiment of the invention, one or more contact-free sensors can be employed within the foot covering of either a biological foot or prosthetic foot, either in addition or as an alternative to contact or pressure sensors. Examples of suitable contact-free sensors include cameras, distance-measuring sensors, and laser scanners. Such sensors, when employed, can be placed in communication with an AWLD controller that uses signals from these sensors to predict and respond to gait events and terrain changes by actuating AWLD in real time. The contact-free sensors can be aligned in any orientation or position either interior or exterior to an associated sock, foot cover, or shoe. With respect to powered exoskeletons and orthosis controllers, contact-free sensors can be aligned in any orientation or position either exterior or interior to an associated exoskeleton or orthosis.
[0063] In one embodiment, at least one non-contact sensor is positioned in a forward orientation at a toe area of a shoe, whereby it is used to predict that the user will ascend stairs or clear an obstacle, as visualized in
[0064] Another embodiment of the invention includes real-time statistical or diagnostic monitoring in AWLDs using kinetic or non-contact sensors. Signals generated using these sensors can be monitored to provide statistical or diagnostic information about the AWLD. Statistical information can include, for example, statistics, step counts, information about power or force output, time spent, and electrical or metabolic work done in various modes, tasks, or states. This can be used to collect information from one user or across many users. Diagnostic information concerns any data regarding intended operation of the device or deviation from intended operation.
Mechanical Design
[0065] Another embodiment of the invention includes an autonomous multi-degree of freedom lower limb prosthesis, orthotic, exoskeleton, or wearable system that relies on signals, features, and pattern recognition on kinetic signals for control, such as an autonomous knee-ankle-foot, transfemoral prosthesis system with four powered/actuated degrees of freedom (DOFs) or powered axes of motion. The embodiment of the four DOF system shown in
[0066] In this embodiment, an open-source FlexSEA bionic control architecture is utilized. This electronics architecture integrates high powered electronics 292 with flexible, high-fidelity sensing. In one embodiment, each actuated degree of freedom include power electronics 292 and high fidelity sensing electronics (referred to as Execute boards) controlled by Cypress Semiconductor PSOC microprocessors. Digital and analog input-output (I/O) functionality on the Execute board include native inertial measurement units, strain gage amplifiers, and expandable generic I/O. Generally, all DOFs are simultaneously connected and controlled with a single high level controller (Management board) 293, based on the STMicrosystems STM32 microprocessor, that fuses all sensors and state information. In this embodiment, the Management board 293 performs the high-level control that includes mode, task, state identification and operations as shown in
[0067] In a specific embodiment, the invention is an ankle-foot prosthesis, having two DOFs. A passive foot prosthesis is shown in
[0068] As that term is understood herein, the term linkage means a mechanical component that transmits bidirectional force with a push-pull action such as push-rod or flexure, a unidirectional tensile component such as a belt, cable, or chain, or a torsional component transmitting rotary motion directly through a rotary element, or a combination of elements such as a roller-cam element.
[0069] In detail, in this embodiment one actuator as shown in
[0070] In the embodiment shown, high-torque, brushless, and direct current (BLDC) split phase sector motors (also referred to as outrunner motors) 291, for example, can be utilized as torque generators. In this embodiment, each actuator consists of one motor controlled by an Execute electronic control board 292, their synchronization controlled by a Manage microprocessor based high-level controller 293. Due to their torque-density, these split phase sector motors enable reduced transmission ratios from those of typically-available prosthetics. The lower reflected inertia and frictional losses of the reduced transmission ratio results in a higher bandwidth, more dynamic, efficient and quiet system, and also enables a more accurate observation of output torque by way of current sensing at the motor power electronics, reducing the need for additional load-cells, specific series compliance and displacement measurement systems.
[0071] In this embodiment, homodirectional or synchronous motion between the left and right push-rods 288 affect ankle rotation for dorsiflexion and plantarflexion (plantarflexion is shown in
[0072] For this embodiment,
[0073] The embodiment of the gimbal as described is more clearly visible in
[0074] In still another embodiment, the invention includes a single DOF foot device (
[0075] In yet another embodiment, in
[0076] In
[0077] One embodiment of the invention is an autonomous four DOF knee-ankle-foot prosthesis system comprising a knee joint with a single actuated DOF, ankle-foot-prosthesis with two actuated DOFs, and prosthetic foot with single actuated DOF. Another embodiment includes: an autonomous three DOF knee-ankle-foot prosthesis system comprising a knee with a single actuated DOF; an ankle-foot prosthesis with two actuated DOFs; and a passive prosthetic foot. Still another embodiment of the invention is an autonomous single DOF knee-ankle-foot prosthesis that includes: a knee with a single actuated DOF; a passive ankle-foot prosthesis; and a passive prosthetic foot. Yet another embodiment of the invention is an autonomous three DOF knee-ankle-foot prosthesis that includes: a passive knee joint; an ankle-foot prosthesis with two actuated DOFs; and a prosthetic foot with one actuated DOF. Still another embodiment of the invention is an autonomous two DOF knee-ankle-foot prosthesis that includes: a passive knee joint; an ankle-foot prosthesis with two actuated DOFs; and a passive prosthetic foot. In another embodiment, the invention is an autonomous three DOF ankle-foot prosthesis that includes: an ankle-foot prosthesis with two actuated DOFs; and a prosthetic foot with one actuated DOF. Another embodiment is an autonomous two DOF ankle-foot prosthesis that includes: an ankle-foot prosthesis with two actuated DOFs and a passive prosthetic foot.
[0078] The following is a description of a demonstration of select embodiments of the invention, and is not intended to be limiting in any way.
EXEMPLIFICATION
[0079] We performed a preliminary study in which we asked six subjects with unilateral transtibial amputations (ages ranged between 28 and 66, heights 1.68 m and 1.90 m, and weights between 130 and 229 lbs, all K4 ambulators) to traverse various terrains while signals were collected from an array of kinetic sensors embedded in an insole on the side of the prosthetic device.
[0080] Data for each subject was collected in several trials each involving between eight and twelve circuits. In each trial, subjects were asked to undergo several circuits involving transitions to and from a staircase and flat ground while wearing a powered transtibial prosthesis aligned to a custom fitted socket via a pylon of appropriate length. Each circuit comprised one complete ascent, turn-around maneuver, descent, and subsequent turn-around, allowing for transitions to and from the terrain in either direction. Stairs terminated in a platform allowing for approximately one complete gait cycle completion after exiting the staircase and before turning around.
[0081] Each trial was conducted such that the subject was visible by at least four motion capture cameras at all times, which were set to a capture rate of 100 Hz. Data were collected from the prosthesis sensors (including an inertial measurement unit and motor and ankle joint encoders) and from resistive pressure sensing insoles developed by Tekscan. All subjects wore a rubber cosmesis over their carbon fiber foot, with pressure sensing insoles positioned between the cosmesis and shoe insole and taped to the latter. Pressure sensors were cut by hand to match the size of the shoe's insole.
[0082] Subjects were asked to begin each trial with a quiet period of static, bilateral stance to establish a reference pressure distribution on the sensor. Additionally, sensors were calibrated using a proprietary method provided by Tekscan software that involved collecting a short trial of unilateral (one-legged) stance on the instrumented leg. All subjects were physically labeled by a full lower body marker set (described in a further section).
[0083] Subjects used the BiOM ankle-foot prosthesis (
[0084] Pressure sensing insoles were part of the F-Scan In-Shoe Analysis System developed by Tekscan. The sensors were originally size 14 (US) and trimmed in accordance with the foot size of each subject. Sensor technology was resistive, with 0.15 mm thickness, 25 sensel per in2 resolution, and 862 KPa pressure range. An example is displayed in
[0085] For each trial, various time varying signals were extracted from the frame data including the centers of pressures, integrated pressures across the ball, heel, and whole foot, and derivatives of these signals. All integrated pressure signals were normalized by the mean maximum value achieved across all flat ground to flat ground steps. Next, all stance phase periods within the trial were identified using a threshold on total integrated force, and the boundaries of each stance window were used to identify foot contact and foot off, respectively. For each stance period, a terrain (either flat ground, upstairs, or downstairs) was defined using motion capture data, which included data about subject and staircase position.
[0086] We then extracted various features for each signal from only the stance phase, including mean, maximum, minimum, range, standard deviation, and initial and final values. Additionally, the initial length of stance was used as a feature. All features were then standardized to zero mean and unit variance across the entire dataset.
[0087] Finally, we employed pattern recognition on the features of each step to predict the labeled terrain of the next step correctly. We were able to attain an accuracy of approximately 86% using a 20-fold cross-validated linear discriminant analysis classifier with empirical prior probabilities on data containing transitions among flat ground, upstairs, and downstairs steps. Complete data for all feature subsets using empirical priors are presented in the
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[0125] The relevant teachings of all patents, published applications and references cited herein are incorporated by reference in their entirety.