[BrainConnexion] - Neurodevice Phase I Trial

Spinal Cord Injuries Clinical Trial

Official title:

Neurodevice Phase I: Wireless Implantable Neurodevice Microsystem for Neuroprosthesis and Neuroscience

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT03811301
• Other study ID #: BrainConnexion
• Status: Active, not recruiting
• Phase: N/A
• Start date: November 21, 2017
• Est. completion date: August 27, 2023

Study information

• Verified date: November 2022
• Source: National Neuroscience Institute
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

This study aims to evaluate the safety of a wireless implantable neurodevice microsystem in tetraplegic patients, as well as the efficacy of the electrodes for long-term recording of neural activities and the successful control of an external device.

Description:

The goal of this study is to develop a miniaturized wireless implantable neurodevice microsystem that records and transmits signals from the motor cortex of tetraplegic patients, bypassing the damaged nervous tissue, to control an external assistive device that restores some form of independence to patients in terms of communication or mobility.

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 5
• Est. completion date: August 27, 2023
• Est. primary completion date: January 27, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 21 Years and older

Eligibility

Inclusion Criteria:

1. 21 years old and older

2. Tetraparesis

3. Written informed consent obtained from the patient or legal representative (in the event where the patient is unable to provide consent) prior to entry into the study in accordance with local EC/IRB regulations and/or other application regulations for surrogate consent.

4. Able to perform the pre-operation Brain Computer Interface training as judged by the research team.

Exclusion Criteria:

1. Significant medical co-morbidities e.g. cardiac disease

2. Bleeding disorders

3. Any contraindication to surgery

4. Other concomitant intracranial pathologies

5. History of seizures or epilepsy disorder

6. Complications of coagulopathy

7. Surgically unfit

8. Significant psychological issues e.g. Depression

9. Poor psychological support

10. Pregnancy

11. No means of communication

12. Any disease, in the opinion of the Investigator, that is unstable or which could jeopardise the safety of the patient If applicable, psychological assessment may be performed prior to selection as the implantation process will be a long a stressful event, requiring a significant degree of patient cooperation and resilience.

Related Conditions & MeSH terms

• Amyotrophic Lateral Sclerosis
• Locked-in Syndrome
• Motor Neuron Disease
• Muscular Dystrophies
• Quadriplegia
• Spinal Cord Injuries
• Tetraplegia
• Tetraplegia/Tetraparesis

Intervention

Device:
• BrainConnexion
A 4.4mm by 4.2mm electrode array is placed onto the surface of the motor cortex which is then connected to a miniaturized neural recording microsystem that transmits signals wirelessly to control an external assistive device. Neural signals are recorded at least once every week for 12 months or longer.

Locations

Country	Name	City	State
Singapore	National Neuroscience Institute	Singapore

Sponsors (5)

Lead Sponsor	Collaborator
National Neuroscience Institute	Institute for Infocomm Research, Institute of Microelectronics, Institute of Molecular and Cell Biology, Nanyang Technological University

Country where clinical trial is conducted

Singapore, 

References & Publications (20)

Aflalo T, Kellis S, Klaes C, Lee B, Shi Y, Pejsa K, Shanfield K, Hayes-Jackson S, Aisen M, Heck C, Liu C, Andersen RA. Neurophysiology. Decoding motor imagery from the posterior parietal cortex of a tetraplegic human. Science. 2015 May 22;348(6237):906-10. doi: 10.1126/science.aaa5417. — View Citation

Cheng, M. Y., Je, M., Tan, K. L., et al. (2013). A low-profile three-dimensional neural probe array using a silicon lead transfer structure. J Micromechanics Microengineering, 23(9), 095013. doi:10.1088/0960-1317/23/9/095013.

Cheng, M. Y., Yao, L., Tan, K. L., Lim, R., Li, P., & Chen, W. (2014). 3D probe array integrated with a front-end 100-channel neural recording ASIC. J Micromechanics Microengineering, 24(12), 125010. doi:10.1088/0960-1317/24/12/125010.

Christopher and Dana Reeve Foundation. Christopher and Dana Reeve Foundation. https://www.christopherreeve.org/. Published 2016.

Collinger JL, Wodlinger B, Downey JE, Wang W, Tyler-Kabara EC, Weber DJ, McMorland AJ, Velliste M, Boninger ML, Schwartz AB. High-performance neuroprosthetic control by an individual with tetraplegia. Lancet. 2013 Feb 16;381(9866):557-64. doi: 10.1016/S0140-6736(12)61816-9. Epub 2012 Dec 17. — View Citation

Hochberg LR, Bacher D, Jarosiewicz B, Masse NY, Simeral JD, Vogel J, Haddadin S, Liu J, Cash SS, van der Smagt P, Donoghue JP. Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature. 2012 May 16;485(7398):372-5. doi: 10.1038/nature11076. — View Citation

Hochberg LR, Serruya MD, Friehs GM, Mukand JA, Saleh M, Caplan AH, Branner A, Chen D, Penn RD, Donoghue JP. Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature. 2006 Jul 13;442(7099):164-71. doi: 10.1038/nature04970. — View Citation

Lee, K., Singh, A., He, J., Massia, S., Kim, B., & Raupp, G. (2004). Polyimide based neural implants with stiffness improvement. Sensors Actuators B Chem,102(1), 67-72. doi: 10.1016/j.snb.2003.10.018.

Libedinsky C, So R, Xu Z, Kyar TK, Ho D, Lim C, Chan L, Chua Y, Yao L, Cheong JH, Lee JH, Vishal KV, Guo Y, Chen ZN, Lim LK, Li P, Liu L, Zou X, Ang KK, Gao Y, Ng WH, Han BS, Chng K, Guan C, Je M, Yen SC. Independent Mobility Achieved through a Wireless Brain-Machine Interface. PLoS One. 2016 Nov 1;11(11):e0165773. doi: 10.1371/journal.pone.0165773. eCollection 2016. — View Citation

Liu X, Zhou J, Wang C, et al. An Ultralow-Voltage Sensor Node Processor With Diverse Hardware Acceleration and Cognitive Sampling for Intelligent Sensing. IEEE Trans Circuits Syst II Express Briefs. 2015;62(12):1149-1153. doi:10.1109/TCSII.2015.2468927.

Rebsamen B, Guan C, Zhang H, Wang C, Teo C, Ang MH Jr, Burdet E. A brain controlled wheelchair to navigate in familiar environments. IEEE Trans Neural Syst Rehabil Eng. 2010 Dec;18(6):590-8. doi: 10.1109/TNSRE.2010.2049862. Epub 2010 May 10. — View Citation

Rosa So, Libedinsky C, Kai Keng Ang, Wee Chiek Clement Lim, Kyaw Kyar Toe, Cuntai Guan. Adaptive decoding using local field potentials in a brain-machine interface. Annu Int Conf IEEE Eng Med Biol Soc. 2016 Aug;2016:5721-5724. doi: 10.1109/EMBC.2016.7592026. — View Citation

Schwarz DA, Lebedev MA, Hanson TL, Dimitrov DF, Lehew G, Meloy J, Rajangam S, Subramanian V, Ifft PJ, Li Z, Ramakrishnan A, Tate A, Zhuang KZ, Nicolelis MA. Chronic, wireless recordings of large-scale brain activity in freely moving rhesus monkeys. Nat Methods. 2014 Jun;11(6):670-6. doi: 10.1038/nmeth.2936. Epub 2014 Apr 28. — View Citation

So RQ, Xu Z, Libedinsky C., Ang KK, Toe KK, Yen SC, Guan CT (2015) Neural Representations of Movement during Brain-Controlled Self-Motion. Conf Proc 7th International IEEE EMBS Conference on Neural Engineering.

Technical specifications for short range devices - Issue 1 Rev 7, Apr 2013. https://www.ida.gov.sg/~/media/Files/PCDG/Licensees/StandardsQoS/RadiocomEquipStd/TSSRD.pdf

Xu Z, Guan CT, So RQ, Ang KK, Toe KK. (2015) Motor Cortical Adaptation Induced by Closed-Loop BCI. Conf Proc 7th International IEEE EMBS Conference on Neural Engineering.

Xu Z, So RQ, Toe KK, Ang KK, Guan C. On the asynchronously continuous control of mobile robot movement by motor cortical spiking activity. Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:3049-52. doi: 10.1109/EMBC.2014.6944266. — View Citation

Yin M, Borton DA, Komar J, Agha N, Lu Y, Li H, Laurens J, Lang Y, Li Q, Bull C, Larson L, Rosler D, Bezard E, Courtine G, Nurmikko AV. Wireless neurosensor for full-spectrum electrophysiology recordings during free behavior. Neuron. 2014 Dec 17;84(6):1170-82. doi: 10.1016/j.neuron.2014.11.010. Epub 2014 Dec 4. — View Citation

Zaaroor M, Kosa G, Peri-Eran A, Maharil I, Shoham M, Goldsher D. Morphological study of the spinal canal content for subarachnoid endoscopy. Minim Invasive Neurosurg. 2006 Aug;49(4):220-6. doi: 10.1055/s-2006-948000. — View Citation

Zou, X., Liu, L., Cheong, J. H., et al. (2013). A 100-Channel 1-mW implantable neural recording IC. IEEE Trans Circuits Syst I Regul Pap, 60(10), 2584-2596. doi:10.1109/TCSI.2013.2249175.

* Note: There are 20 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	The number of serious adverse events (SAEs) and adverse events (AEs) reported per patient 12 months post-implantation.	The primary objective of this study is to determine the safety of the device. This will be assessed based on the number of SAEs and AEs reported for each patient during the 12 months post-implantation evaluation. This measure will considered a success if the device is not removed for safety reasons within 12-months after implantation.	6 months post-implant
Secondary	The signal quality of the electrodes for long-term recording of neural signals.	Signal quality will be measured by the number of channels with identifiable single units tracked across each day for 12 months.	Day 1 to Day 365 post-implant
Secondary	Decoding accuracy per training session.	Decoding accuracy will be measured in percentage (%).	Day 1 to Day 365 post-implant
Secondary	Number of successful trials per session	The number of successful trials per training session will be measured in percentage (%).	Day 1 to Day 365 post-implant
Secondary	Time taken to complete each trial per session	This will be measured in seconds (s).	Day 1 to Day 365 post-implant