Multi-Mode Above-Knee Prosthesis Controller

Grimes, D.L.; Flowers, Woodie C.

doi:10.1016/b978-0-08-029350-9.50011-6

Cited by 22 publications

(30 citation statements)

References 6 publications

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“…Although alternative approaches have been explored in rehabilitation robotics [13], [14], tracking predefined joint patterns remains the state of the art in the control of powered artificial legs [15]- [17]. For instance, current leg prostheses mimic human joint impedances that have been recorded in experiments [16].…”

Section: Introductionmentioning

confidence: 99%

Robust swing leg placement under large disturbances

Desai

Geyer

2012

2012 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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Swing leg placement is vital to dynamic stability in legged robots and animals. The most common approaches to generating swing leg motions in robotics use either position or impedance tracking of defined joint trajectories. While these approaches suffice in humanoids, they severely limit swing leg placement under large disturbances in prosthetic limbs, for which stabilizing reactions cannot be planned centrally. Rather than careful central planning, animals and humans seem to rely on local feedback control for reliable swing leg placement. Motivated by this observation, we here present an alternative for generating swing leg motions. We develop a local swing leg control that takes advantage of segment interactions to achieve robust leg placement under large disturbances while generating trajectories and joint torque patterns similar to those patterns observed in human walking and running. The results suggest the identified control as a powerful alternative to existing swing leg controls in humanoid and rehabilitation robotics.

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Section: Introductionmentioning

confidence: 99%

Robust swing leg placement under large disturbances

Desai

Geyer

2012

2012 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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“…Regarding the former, [10] describes the development of an electro-hydraulically powered knee prosthesis, developed as a laboratory test bed for studying the control of powered knee joints during walking. This prosthesis was utilized to develop an echo control approach, in which the authors instrumented the sound-side knee (of a unilateral amputee) with a position sensor, and used a modified version of the measured knee angle profile on the powered prosthesis side one half cycle later, which they term “modified echo control” [11, 12]. Ossur, a prosthetics company, recently introduced a self-contained (battery-powered) powered knee prosthesis, in which they similarly instrument the sound side leg (with accelerometers) and also utilize an echo type approach [13].…”

Section: Introductionmentioning

confidence: 99%

“…Recently, an electromyography based pattern recognizer for classifying locomotion modes using artificial neural networks and linear discriminant analysis is presented in [16]. Regarding the echo control approaches incorporated in [10–12, 17], an obvious drawback is that the sound-side (or unaffected) leg must be instrumented, which requires the user to don and doff additional instrumentation. The echo control approach presumably also restricts the use of the prosthesis to unilateral amputees and also presents a problem for “odd” numbers of steps, in which an echoed step is undesirable.…”

Section: Introductionmentioning

confidence: 99%

Multiclass Real-Time Intent Recognition of a Powered Lower Limb Prosthesis

Varol

Sup

Goldfarb

2010

IEEE Trans. Biomed. Eng.

385

254

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This paper describes a control architecture and intent recognition approach for the real-time supervisory control of a powered lower limb prosthesis. The approach infers user intent to stand, sit, or walk, by recognizing patterns in prosthesis sensor data in real-time, without the need for instrumentation of the sound-side leg. Specifically, the intent recognizer utilizes time-based features extracted from frames of prosthesis signals, which are subsequently reduced to a lower dimensionality (for computational efficiency). These data are initially used to train intent models, which classify the patterns as standing, sitting, or walking. The trained models are subsequently used to infer the user's intent in real-time. In addition to describing the generalized control approach, this paper describes the implementation of this approach on a single unilateral transfemoral amputee subject, and demonstrates via experiments the effectiveness of the approach. In the real-time supervisory control experiments, the intent recognizer identified all 90 activity mode transitions, switching the underlying middle level controllers without any perceivable delay by the user. The intent recognizer also identified six activity mode transitions, which were not intended by the user. Due to the intentional overlapping functionality of the middle level controllers, the incorrect classifications neither caused problems in functionality, nor were perceived by the user.

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“…The finite state intent recognizer ascertains locomotion phase transitions and then applies the suitable control architecture. 62 The finite state machine that implements the finite state control architecture adheres to a series of rules to define the appropriate states, which are established by pre-determined threshold bounds. 63 Herr and Wilkenfield utilized mechanical sensors with a user-adaptive control scheme to advance the biological realism of gait with a trans-femoral prosthesis.…”

Section: Control Architecture Of a Powered Prosthesismentioning

confidence: 99%

Advances Regarding Powered Prosthesis for Transtibial Amputation

LeMoyne

2015

J. Mech. Med. Biol.

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The necessity for developing advanced prostheses are apparent in light of projections that the forecast for the number of people enduring amputation will double by the year 2050. The transtibial powered prosthesis that enables positive mechanical work about the ankle during the powered plantar flexion aspect of stance phase constitutes a paradigm shift in available transtibial prostheses. The objective of the review is to advocate the state of the art regarding the transtibial powered prosthesis. The historic origins of the prosthesis and motivations for amputation are clarified. The phases of gait and the compensatory mechanisms and asymmetries inherent with passive transtibial prostheses are described. The three general classes of transtibial prosthesis (passive, energy storage and return and powered prostheses) are defined. Subsystems that are integral to the powered prosthesis are explained, such as the series elastic actuator and control architecture. Gait analysis systems and their role for the test and evaluation of energy storage and return and powered prostheses are demonstrated. Future advanced concepts; such as the integration of titin into novel muscle models that account for force enhancement and force depression including their implications for cutting edge bio-inspired actuators are elucidated. The review accounts for the evolution of the prosthetic device with regards to the scope of transtibial amputation and assesses the current state-of-the-art.

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Multi-Mode Above-Knee Prosthesis Controller

Cited by 22 publications

References 6 publications

Robust swing leg placement under large disturbances

Robust swing leg placement under large disturbances

Multiclass Real-Time Intent Recognition of a Powered Lower Limb Prosthesis

Advances Regarding Powered Prosthesis for Transtibial Amputation

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