Babak Hejrati

Dr. Babak Hejrati

orcid

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 August 2017 in IEEE Transactions on Neural Systems and Rehabilitation Engineering
Verified
Journal Article
Open access
BHBabak Hejrati
Babak Hejrati
AMAndrew S. Merryweather
Andrew S. Merryweather
JAJake J. Abbott
Jake J. Abbott
Gait rehabilitation is often focused on the legs and overlooks the role of the upper limbs. However, a variety of studies have demonstrated the importance of proper arm swing both during healthy walking and during rehabilitation. In this paper, we describe a method for generating proper arm-swing trajectories in real time using only measurements of the angular velocity of a person's thighs, to be used during gait rehabilitation with self-selected walking speed. A data-driven linear time-invariant transfer function is developed, using frequency-response methods, which captures the frequency-dependent magnitude and phase relationship between the thighs' angular velocities and the arm angles (measured at the shoulder, in the sagittal plane), using a data set of 30 healthy adult subjects. We show that the proposed method generates smooth trajectories for both healthy individuals and patients with mild to moderate Parkinson disease. The proposed method can be used in future robotic devices that integrate arm swing in gait rehabilitation of patients with walking impairments to improve the efficacy of their rehabilitation.

27 February 2023 in IEEE Transactions on Neural Systems and Rehabilitation Engineering
Verified
Journal Article
Open access
MNMohsen Alizadeh Noghani
Mohsen Alizadeh Noghani
THTanzid Hossain
Tanzid Hossain
BHBabak Hejrati
Babak Hejrati
Due to the neural coupling between upper and lower limbs and the importance of interlimb coordination in human gait, focusing on appropriate arm swing should be a part of gait rehabilitation in individuals with walking impairments. Despite its vital importance, there is a lack of effective methods to exploit the potential of arm swing inclusion for gait rehabilitation. In this work, we present a lightweight and wireless haptic feedback system that provides highly synchronized vibrotactile cues to the arms to manipulate arm swing and investigate the effects of this manipulation on the subjects’ gait in a study with 12 participants (20-44 years). We found the developed system effectively adjusted the subjects’ arm swing and stride cycle times by significantly reducing and increasing those parameters by up to 20% and 35%, respectively, compared to their baseline values during normal walking with no feedback. Particularly, the reduction of arms’ and legs’ cycle times translated into a substantial increase of up to 19.3% (on average) in walking speed. The response of the subjects to the feedback was also quantified in both transient and steady-state walking. The analysis of settling times from the transient responses revealed a fast and similar adaptation of both arms’ and legs’ movements to the feedback for reducing cycle time (i.e., increasing speed). Conversely, larger settling times and the time differences between arms’ and legs’ responses were observed due to feedback for increasing cycle times (i.e., reducing speed). The results clearly demonstrate the potential of the developed system to induce different arm-swing patterns as well as the ability of the proposed method to modulate key gait parameters through leveraging the interlimb neural coupling, with implications for gait training.

29 May 2023 in Human Movement Science
Verified
Journal Article
Closed access
THTanzid Hossain
Tanzid Hossain
MNMohsen Alizadeh Noghani
Mohsen Alizadeh Noghani
BSBen Sidaway
Ben Sidaway
BHBabak Hejrati
Babak Hejrati

2 July 2021 in IEEE Robotics and Automation Letters
Verified
Journal Article
Closed access
MNMohsen Alizadeh Noghani
Mohsen Alizadeh Noghani
mohsen shahinpoormohsen shahinpoor
mohsen shahinpoor
BHBabak Hejrati
Babak Hejrati
This paper presents a novel vibrotactile haptic system controlled by a smartphone that can be used for gait training of older adults. Compared to previous works, the system's modularity as well as its smartphone-based controller and user interface can enhance its usability and promote regular gait training of users during their daily living. Given the prevalence of reduced stride length and speed in older adults, we developed a biomechanical data-driven approach to enable improving those outcomes via modifying their underlying surrogates. A subject study was performed by recruiting 12 young participants (19-39 years) to assess the efficacy of the haptic system and our approach based on biomechanical surrogates. It was found that the participants could significantly increase their thigh and shank extensions (i.e., the surrogates) via the feedback provided by our system, and those increases resulted in higher values of their stride length and walking speed. The results provide a clear proof-of-concept for the developed biomechanics-driven haptic system for gait training of older adults to potentially improve their mobility and living independence.

27 December 2024 in Annals of Biomedical Engineering
Verified
Journal Article
Closed access
PDF file
IKInes Khiyara
Ines Khiyara
BSBen Sidaway
Ben Sidaway
BHBabak Hejrati
Babak Hejrati

1 October 2021 in Human Movement Science
Verified
Journal Article
Closed access
JBJacob Bloom
Jacob Bloom
BHBabak Hejrati
Babak Hejrati