Rehab Centers: Detection of Movements With Attention or Distraction to the Motor Task During Robot-Assisted Passive Movements of the Upper Limb.
Detection of movements with attention or distraction to the motor task during robot-assisted passive movements of the upper limb.
Filed under: Rehab Centers
Conf Proc IEEE Eng Med Biol Soc. 2012 Aug; 2012: 6410-3
Antelis JM, Montesano L, Giralt X, Casals A, Minguez J
Robot-assisted rehabilitation therapies usually focus on physical aspects rather than on cognitive factors. However, cognitive aspects such as attention, motivation, and engagement play a critical role in motor learning and thus influence the long-term success of rehabilitation programs. This paper studies motor-related EEG activity during the execution of robot-assisted passive movements of the upper limb, while participants either: i) focused attention exclusively on the task; or ii) simultaneously performed another task. Six healthy subjects participated in the study and results showed lower desynchronization during passive movements with another task simultaneously being carried out (compared to passive movements with exclusive attention on the task). In addition, it was proved the feasibility to distinguish between the two conditions.
HubMed – rehab
Recognition of household and athletic activities using smartshoe.
Filed under: Rehab Centers
Conf Proc IEEE Eng Med Biol Soc. 2012 Aug; 2012: 6382-5
Edgar SR, Fulk GD, Sazonov ES
The ability to provide real time feedback concerning a person’s activity level and energy expenditure can be beneficial for improving activity levels of individuals. Examples include biofeedback systems used for body weight and physical activity management and biofeedback systems for rehabilitation of stroke patients. A critical aspect of any such system is being able to accurately classify data in real-time so that active and timely feedback can be provided. In the paper we demonstrate feasibility of real-time recognition of multiple household and athletic activities on a cell phone using the data collected by a wearable sensor system consisting of SmartShoe sensor and a wrist accelerometer. The experimental data were collected for multiple household and athletic activities performed by a healthy individual. The data was used to train two neural networks, one to be used primarily for sedentary individuals and one for more active individuals. Classification of household activities including ascending stairs, descending stairs, doing the dishes, vacuuming, and folding laundry, achieved 89.62% average accuracy. Classification of athletic activities such as jumping jacks, swing dancing, and ice skating, was performed with 93.13% accuracy. As proof of real-time processing on a mobile platform the trained neural network for healthy individuals was timed and required less than 4ms to perform each feature vector construction and classification.
HubMed – rehab
Vestibular physical therapy intervention: utilizing a computer assisted rehabilitation environment in lieu of traditional physical therapy.
Filed under: Rehab Centers
Conf Proc IEEE Eng Med Biol Soc. 2012 Aug; 2012: 6141-4
Gottshall KR, Sessoms PH, Bartlett JL
Advanced technology such as virtual reality or immersive environments increases the complexities and challenges therapists can impose on their patients. In this study, four patients with mild traumatic brain injury utilized a Computer Assisted Rehabilitation Environment (CAREN) in place of traditional vestibular physical therapy. Patients visited the CAREN twice weekly for 6 weeks. Therapy sessions included a variety of applications that tasked the cognitive and physical capabilities of individual patients. After the 6 weeks, all patients showed improvement on balance, gait and visual measures. Virtual reality based therapy is an engaging and effective tool to treat patients with deficiencies related to a prior brain injury.
HubMed – rehab
On the design of ergonomic wearable robotic devices for motion assistance and rehabilitation.
Filed under: Rehab Centers
Conf Proc IEEE Eng Med Biol Soc. 2012 Aug; 2012: 6124-7
Chiri A, Cempini M, De Rossi SM, Lenzi T, Giovacchini F, Vitiello N, Carrozza MC
The appropriate ergonomic design of a wearable robotic device is critical for the effectiveness of the device itself. In this paper we identified two key requirements for a structural ergonomics: the correct kinematic compatibility with the human limb and a comfortable and adaptable physical human-robot interface. We then show how the aforementioned requirements have been faced and implemented in the mechanical design of two wearable devices for elbow and hand rehabilitation, both developed at The BioRobotics Institute of Scuola Superiore Sant’ Anna.
HubMed – rehab
Beyond the standard clinical rating scales: Fine-grained assessment of post-stroke motor functionality using wearable inertial sensors.
Filed under: Rehab Centers
Conf Proc IEEE Eng Med Biol Soc. 2012 Aug; 2012: 6111-5
Zhang M, Lange B, Chang CY, Sawchuk AA, Rizzo AA
Accurate motor function assessment of post-stroke patients plays a critical role in their rehabilitation interventions. In this paper, we propose an approach to use wearable inertial sensing technology to quantitatively evaluate the patients’ motor behavior. Different from existing wearable motor function assessment techniques that focus on building mapping functions that correlate sensed movement signals to the standard clinical rating scales, our approach provides a fine-grained assessment by capturing detailed patterns contained in the patients’ movements. We collected data on three subjects including two post-stroke patients who have varying degrees of upper extremity hemiparesis. Our experimental results validate our approach and demonstrate that the captured patterns can be used to complement the standard clinical scores to provide fine-grained motor function assessment and help clinicians to track patients’ gradual progress during rehabilitation.
HubMed – rehab
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