Real-time gait event detection using wearable sensors

Hanlon, Michelle; Anderson, Ross

doi:10.1016/j.gaitpost.2009.07.128

Cited by 161 publications

(90 citation statements)

References 28 publications

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“…Control and Evaluation Detection algorithms based on machine learning and rulebased heuristics are used to identify gait events/phases [6,9,15,[17][18][19][20]. Catalfamo et al [9] evaluated the detection of IC and end of the contact (foot off ) using a single gyroscope on the shank which was validated with seven control subjects walking on level ground and an inclined surface.…”

Section: A Real-time Gait Event Detection For Lower Limb Prosthesismentioning

confidence: 99%

“…Such footswitches are suitable for obtaining on/off information, though not appropriate for precise analog measurements [6]. However, they are susceptible to mechanical failure, have generally poor durability and low cosmetic acceptance [7].…”

Section: Introductionmentioning

confidence: 99%

“…However, they are susceptible to mechanical failure, have generally poor durability and low cosmetic acceptance [7]. Among wearable sensors, accelerometers and gyroscopes are being deployed at different body locations for long-term monitoring of human gait [3,[6][7][8][9][10][11][12][13]. Recent advancements allow these sensors to be miniaturized, with faster processing capability and higher memory capacities to support outdoor applications [9].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Real-Time Gait Event Detection for Lower Limb Prosthesis Control and Evaluation

Maqbool

Husman

Awad

et al. 2017

IEEE Trans. Neural Syst. Rehabil. Eng.

104

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Abstract-Lower extremity amputees suffer from mobility limitations which will result in a degradation of their quality of life. Wearable sensors are frequently used to assess spatiotemporal, kinematic and kinetic parameters providing the means to establish an interactive control of the amputee-prosthesisenvironment system. Gait events and the gait phase detection of an amputee's locomotion are vital for controlling lower limb prosthetic devices. The paper presents an approach to real-time gait event detection for lower limb amputees using a wireless gyroscope attached to the shank when performing level ground and ramp activities. The results were validated using both healthy and amputee subjects and showed that the time differences in identifying Initial Contact (IC) and Toe Off (TO) events were larger in a transfemoral amputee when compared to the control subjects and a transtibial amputee (TTA). Overall, the time difference latency lies within a range of ± 50 ms while the detection rate was 100% for all activities. Based on the validated results, the IC and TO events can be accurately detected using the proposed system in both control subjects and amputees when performing activities of daily living and can also be utilized in the clinical setup for rehabilitation and assessing the performance of lower limb prosthesis users.

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Section: A Real-time Gait Event Detection For Lower Limb Prosthesismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Real-Time Gait Event Detection for Lower Limb Prosthesis Control and Evaluation

Maqbool

Husman

Awad

et al. 2017

IEEE Trans. Neural Syst. Rehabil. Eng.

104

View full text Add to dashboard Cite

show abstract

“…Many control algorithms have been implemented using machine learning techniques and simple rule-based approaches [3,12,13] to identify gait phases/events. However, none of the previous studies have dealt with transfemoral amputees (TFA).…”

Section: Introductionmentioning

confidence: 99%

Towards Intelligent Lower Limb Prostheses with Activity Recognition

Maqbool

Mehryar

Husman

et al. 2015

Towards Autonomous Robotic Systems

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Abstract. User's volitional control of lower limb prostheses is still challenging task despite technological advancements. There is still a need for amputees to impose their will upon the prosthesis to drive in an accurate and interactive fashion. This study represents a brief review on control strategies using different sensor modalities for the purpose of phases/events detection and activity recognition. The preliminary work that is associated with middle-level control shows a simple and reliable method for event detection in real-time using a single inertial measurement unit. The outcome shows promising results.

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“…In addition, they are widely used for rehabilitation during assisted gait and for FES synchronization during walking [11], and to synchronize the activity of exoskeletons [12]. Compared to a footswitch system, accelerometers have a lower accuracy (mean absolute error of 2.4 ms2.1 ms for the footswitch system compared to 9.5 ms9.0 ms for the accelerometer system) [13]. Furthermore, determining temporal parameters using accelerometers, despite their portability, requires the use of correction factors and intense mathematical processing through specific computational algorithms, a fact that complicates the use of real time results [14,15].…”

Section: Introductionmentioning

confidence: 99%

Low-cost piezoelectric footswitch system for measuring temporal parameters during walking

Balbinot

Schuch

Zaro

et al. 2014

IJET

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Human walking is one of the most investigated biomechanical events, and gait analysis depends on accurate measurement of heel strike (HS) and toe off (TO). The purpose of this study was to construct and validate a low-cost footswitch system for the measurement of temporal gait parameters. Ten young healthy subjects participated of the validation and test of the footswitch system with two different footwear, Bland-Altman analysis showed 98% and 95% of validation data within the limits of agreement, for HS and TO respectively (mean difference of 16ms±1ms and 20ms±9ms) and the temporal parameters measured during treadmill walking at a speed of 4.5km.h -1 showed results similar to those found in the literature for normal walking. The outcomes confirm low CoVs for the instrumented athletic and instability shoe, respectively: (1.52±0.61)% and (1.90±0.73)% for contact time, (2.17±0.95)% and (2.57±0.95)% for balance time, (0.84±0.28)% and (1.12±0.53)% for stride time. The low-cost footswitch system described and validated in the present study has an important practical applicability, mostly for emerging and developing countries biomechanics labs.

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Real-time gait event detection using wearable sensors

Cited by 161 publications

References 28 publications

A Real-Time Gait Event Detection for Lower Limb Prosthesis Control and Evaluation

A Real-Time Gait Event Detection for Lower Limb Prosthesis Control and Evaluation

Towards Intelligent Lower Limb Prostheses with Activity Recognition

Low-cost piezoelectric footswitch system for measuring temporal parameters during walking

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