Stardust: neurological rehabilitation trainer
Embedded Files
Biomechanical monitoring for medicine
Stardust is a wearable glove specifically designed for the neurological rehabilitation training, equipped with properietay firmware, wireless transmission and integrated sensors.
The Stardust glove is the culmination of the eponymous project, developed in collaboration with the Institute of Development, Aging and Cancer - IDAC (Kawashima Lab) at Tohoku University (Japan).
The "Stardust" Project received funding from the Italian Ministry of Foreign Affairs and International Cooperation.
New frontiers in neuro rehabilitation
Different brain regions are responsible for managing body movements and sensations. When specific areas of the brain are damaged due to neurological conditions associated with aging or traumatic events, individuals may experience severe limitations in controlling movements, speaking, seeing, or feeling.
For instance, following a stroke, patients often encounter significantly reduced mobility and partial paralysis of limbs.
Traditional rehabilitative methods typically involve extensive practice of motor tasks under the supervision of therapists.
However, neuropsychology is now advancing innovative multisensory rehabilitation techniques facilitated by wearable devices and sensors.
This progress is driven by the observed correlation between movements and the concept of "body ownership".
Essentially, when we learn a motor task using one hand, the learning is automatically transferred to the other hand (known as motor learning). This principle can be extended to address impaired body functions.
Towards engineering specifications
The neurological scientists provide a range of training tests used to monitor and check the progress of the patient.
These trainings are converted to specific physical parameters to be measured and, consequently, to the more suitable sensor for wearable application.
The Stardust glove is equipped with eight force and bending tests for the complete monitoring of the hand kinematics.
Electronics miniaturization
The S3 team designs and develops PCBs for controlling and managing sensing operations, data storage, transmission, and power supply.
The initial prototype (a) is constructed on a larger scale for compatibility checks before being miniaturized into the portable version (b).
User friendly interface
The non-specialized user can seamlessly engage with Stardust through the custom interface we've meticulously crafted.
Choosing the training mode is as simple as selecting from a list of clinical sessions.
Our software intuitively identifies the sensor groups to activate based on your selection.
Once the device is connected via Bluetooth and the battery level is confirmed, training commences, capturing and storing biomechanical parameters on your PC in real-time.
Real-time biomechanical measurements
Depending on the training, Stardust provides time-related measurements of finger bending and force. Interpreting this data and tracking its evolution throughout the rehabilitation process allows for quantifying the patient's progress.
This goes beyond the qualitative assessments typically conducted by therapists lacking specialized devices like Stardust.
G. De Pasquale, V. Ruggeri, “Sensing strategies in wearable bio-mechanical systems for medicine and sport: a review”, Journal of Micromechanics and Microengineering, vol. 29 (10), 103001, 2019. DOI: 10.1088/1361-6439/ab2f24. Link
G. De Pasquale, L. Mastrototaro, V. Ruggeri, “Wearable sensing systems for biomechanical parameters monitoring”, Materials Today: Proceedings, vol. 7 (1), p. 560-565, 2019. DOI: 0.1016/j.matpr.2018.12.008. Link
G. De Pasquale, L. Mastrototaro, “Glove-based systems for medical applications: review of recent advancements”, Journal of Textile Engineering & Fashion Technology, vol. 4 (3), p. 286-295, 2018. DOI: 10.15406/jteft.2018.04.00153. Link
G. De Pasquale, V. Ruggeri, “Integrated sensing system for upper limbs in neurologic rehabilitation”, Procedia Structural Integrity, vol. 12, p. 82-86, 2018. DOI: 10.1016/j.prostr.2018.11.104. Link
G. De Pasquale, L. Mastrototaro, L. Pia, D. Burin, “Wearable system with embedded force sensors for neurologic rehabilitation trainings”, proc. Symp. on Design, Testing, Integration, and Packaging of MEMS/MOEMS (DTIP), Rome (Italy), 22-25 May 2018. DOI: 10.1109/DTIP.2018.8394187. Link
G. De Pasquale, A. Mura, “Accelerated lifetime tests on e-textiles: Design and fabrication of multifunctional test bench”, Journal of Industrial Textiles, vol. 47 (8), p. 1925-1943, 2018. DOI: 10.1177/1528083717714483. Link
G. De Pasquale, A. Mura, “Electro-mechanical endurance tests on smart fabrics under controlled axial and friction forces”, Procedia Structural Integrity, vol. 8, p. 220-226, 2018. DOI: 10.1016/j.prostr.2017.12.024. Link
G. De Pasquale, V. Ruggeri, “Sistema di misura integrato per arti superiori in riabilitazioni neuro-motorie”, proc. AIAS Conference, Villa San Giovanni (Italy), 5-8 September 2018.
G. De Pasquale, A. Mura, “Macchina per test accelerati di affidabilità su tessuti intelligenti”, proc. AIAS Conference, Pisa (Italy), 6-9 September 2017.
G. De Pasquale, “Artificial human joint for the characterization of piezoelectric transducers in self-powered telemedicine applications”, Meccanica, vol. 51, p. 2259-2275, 2016. DOI: 10.1007/s11012-016-0359-5. Link
Page updated
Google Sites
Report abuse