Science

Real-world data and advanced AI inform the science of brain health

Overview

The Learning Corp has taken an innovative approach to digital therapeutics for brain health.

It all started a few years ago with Constant Therapy. That’s when we gave patients direct access to our health and wellness app so they could get a personalized, data-driven course of therapy on demand, and we could learn from their experience to refine it.

Since then, the technology we’ve used, and the real-world evidence we’ve generated from the 110 million exercises users have completed, have formed the basis of numerous randomized clinical trials, and informed our broader clinical approach. Today, every digital therapeutic we develop starts with this real-world evidence phase. Because testing and developing products in the real world, with real people, gives us the fastest path to empowering patients, and the foundation for innovation in digital therapeutics.

Pipeline

Constant Therapy is the discovery platform for developing and delivering our digital therapeutics. It is the engine generating the real-world evidence that directs our approach to differentiated, disease-specific products. It can be customized for care delivery, and can be used or adapted for investigational clinical trials.

Our scientific areas of investigation are CNS disorders involving speech, language, and/or cognitive deficits including acquired brain injuries (stroke, TBI), mild cognitive impairment (MCI), mild Alzheimer’s disease, multiple sclerosis, Parkinson’s disease, major depressive disorder and epilepsy.

About Constant Therapy

  • Mobile application: 24/7 access to clinically-proven exercises that can be used anytime, anywhere.
  • Ease of use: Interface intentionally designed for quick onboarding and simple navigation.
  • Evidence-based practice library: More than 14 categories, 80+ exercises with up to 12 levels of difficulty in domains of speech, language and cognition.
  • Personalized care: Patented NeuroPerformance Engine™ (NPE) uses AI and data analytics to deliver a customized exercise program tailored to user progress, with real-time performance monitoring.

Clinical research using Constant Therapy

A number of randomized clinical trials and retrospective studies using Constant Therapy demonstrate the benefit of delivering personalized therapy on a digital platform.

View scientific research using Constant Therapy
  1. Godlove, J., Anantha, V., Advani, M., Des Roches, C., Kiran, S. Comparison of therapy practice at home and in the clinic: A retrospective analysis of the Constant Therapy platform data set. Frontiers in Neurology. doi: 10.3389/fneur.2019.00140
  2. Kiran S, Godlove J, Advani M, Anantha V. Personalizing rehabilitation for stroke survivors: a big data approach. Presented at: International Stroke Conference; February 22-24, 2017; Houston, TX.
  3. Des Roches CA, Mitko A, Kiran S. Relationship between self-administered cues and rehabilitation outcomes in individuals with aphasia: understanding individual responsiveness to a technology-based rehabilitation program. Front Hum Neurosci. 2017;11:07. doi:10.3389/fnhum.2017.00007.
  4. Mallet KH, Shamloul RM, Corbett D, et al. RecoverNow: Feasibility of a mobile tablet-based rehabilitation intervention to treat post-stroke communication deficits in the acute care setting. PLoS One. 2016;11(12):e0167950. doi:10.1371/journal.pone.0167950.
  5. Glynn P, Eom S, Zelko F, Koh S. Feasibility of a mobile cognitive intervention in childhood absence epilepsy. Front Hum Neurosci. 2016;10:575. doi:10.3389/fnhum.2016.00575.
  6. Postman WA. Computer-mediated cognitive-communicative intervention for residents with dementia in a special care unit: an exploratory investigation. Perspectives of the ASHA Special Interest Groups. 2016;1(SIG 15):68-78. doi:10.1044/persp1.SIG15.68.
  7. Mark J, Onaral B, Ayaz H. Evaluating neural correlates of constant therapy neurorehabilitation task battery: an fNIRS pilot study. Presented at: 18th International Conference on Human-Computer Interaction; July 17-22, 2016; Toronto, Ontario, Canada.
  8. Kiran S. How does severity of aphasia influence individual responsiveness to rehabilitation? Using big data to understand theories of aphasia rehabilitation. Semin Speech Lang. 2016;37(1):48-59. doi:10.1055/s-0036-1571358.
  9. Des Roches CA, Balachandran I, Ascenso E, Tripodis Y, Kiran S. Effectiveness of an impairment-based individualized rehabilitation program using an iPad-based software platform. Front Hum Neurosci. 2015;8:1015. doi:10.3389/fnhum.2014.01015.
  10. Kiran S, Des Roches CA, Balachandran I, Ascenso E. Development of an impairment-based individualized treatment workflow using an iPad-based software platform. Semin Speech Lang. 2014;35(1):38-50. doi:10.1055/s-0033-1362995.
  11. Kiran S. Detecting small and large scale fluctuations in language and cognitive performance: a longitudinal rehabilitation case study. Int J Phys Med Rehabil. 2014;2(suppl):203. doi:10.4172/2329-9096.1000203.
Posters
  1. Kiran, S., Gerst, K., Godlove, J., Anantha, V., Dubas, E. (2019, February). Understanding optimal dosage frequency and patient engagement on improving outcomes using digital therapy. International Stroke Conference, Honolulu.
  2. Dubas, E., Godlove, J., Kiran, S., Gerst, K. (2019, March). Understanding enablers and barriers to using technology with people with aphasia.  Aphasia Access Leadership Summit, Baltimore.
  3. Godlove, J., Dubas, E., Advani M.,Poskanzer D., Kiran, S. (2019, March). Using technology to understand patient reported outcomes of life participation after aphasia. Aphasia Access Leadership Summit, Baltimore.
  4. Godlove J., Kiran S. (2017, October). Understanding the effect of patient severity on aphasia rehabilitation outcomes. American Congress of Rehabilitation Medicine (ACRM) Annual Conference, Atlanta.
  5. Godlove, J., Anantha, V., Kiran, S. (2017, October). Is home based therapy as effective in-clinic therapy for patients with aphasia. American Congress of Rehabilitation Medicine (ACRM) Conference, Atlanta.
View the clinical evidence behind Constant Therapy
  1. Abel S, Willmes K, Huber W. Model‐oriented naming therapy: testing predictions of a connectionist model. Aphasiology. 2007;21(5):411-447. doi:10.1080/02687030701192687.
  2. Annoni JM, Khateb A, Custodi MC, Debeauvais V, Michel CM, Landis T. Advantage of semantic language therapy in chronic aphasia: a study of three cases. Aphasiology. 1998;12(12):1093-1105. doi:10.1080/02687039808249475.
  3. Ball AL, de Riesthal M, Breeding, VE, Mendoza DE. Modified ACT and CART in severe aphasia. Aphasiology. 2011;25(6-7):836-848. doi:10.1080/02687038.2010.544320.
  4. Baldwin VN, Powell T. Google Calendar: A single case experimental design study of a man with severe memory problems. Neuropsychol Rehabil. 2015;25(4):617-636. doi:10.1080/09602011.2014.956764.
  5. Beeson PM, Egnor H. Combining treatment for written and spoken naming. J Int Neuropsychol Soc. 2006;12(6):816-827. doi:10.1017/S1355617706061005.
  6. Beeson PM, Rising K, Kim ES, Rapcsak SZ. A novel method for examining response to spelling treatment. Aphasiology. 2008;22(7-8):707-717. doi:10.1080/02687030701800826.
  7. Beeson PM, Hirsch FM, Rewega MA. Successful single-word writing treatment: experimental analyses of four cases. Aphasiology. 2002;16(4-6):473-491. doi:10.1080/02687030244000167.
  8. Beeson PM, Rising K, Volk J. Writing treatment for severe aphasia: who benefits? J Speech Lang Hear Res. 2003;46(5):1038-1060. doi:10.1044/1092-4388(2003/083).
  9. Berryman A, Rasavage K, Politzer T. Practical clinical treatment strategies for evaluation and treatment of visual field loss and visual inattention. NeuroRehabilitation. 2010;27(3):261-268. doi:10.3233/NRE-2010-0607.
  10. Brunsdon R, Nickels L, Coltheart M, Joy P. Assessment and treatment of childhood topographical disorientation: a case study. Neuropsychol Rehabil. 2007;17(1):53-94. doi:10.1080/09602010600562575.
  11. Cicerone KD. Remediation of “working attention” in mild traumatic brain injury. Brain Inj. 2002;16(3):185-195. doi:10.1080/02699050110103959.
  12. Cipriani G, Bianchetti A, Trabucchi M. Outcomes of a computer-based cognitive rehabilitation program on Alzheimer’s disease patients compared with those on patients affected by mild cognitive impairment. Arch Gerontol Geriatr. 2006;43(3):327-335. doi:10.1016/j.archger.2005.12.003.
  13. Corsten S, Mende M, Cholewa J, Huber W. Treatment of input and output phonology in aphasia: a single case study. Aphasiology. 2007;21(6-8):587-603. doi:10.1080/02687030701192034.
  14. Delazer M, Bodner T, Benke T. Rehabilitation of arithmetical text problem solving. Neuropsychological Rehabilitation. 1998;8(4):401-412. doi:10.1080/713755584.
  15. Doesborgh SJ, van de Sandt-Koenderman MW, Dippel DW, van Harskamp F, Koudstaal PG, Visch-Brink EG. Effects of semantic treatment on verbal communication and linguistic processing in aphasia after stroke: a randomized controlled trial. Stroke. 2004;35(1):141-146. doi:10.1161/01.STR.0000105460.52928.A6.
  16. Domahs F, Bartha-Doering L, Delazer M. Rehabilitation of arithmetic abilities: different intervention strategies for multiplication. Brain and Language. 2003;87(1):165-166. doi:10.1016/S0093-934X(03)00252-9.
  17. Domahs F, Zamarian L, Delazer M. Sound arithmetic: auditory cues in the rehabilitation of impaired fact retrieval. Neuropsychol Rehabil. 2008;18(2):160-181. doi:10.1080/09602010701505648.
  18. Drew RL, Thompson CK. Model-based semantic treatment for naming deficits in aphasia. J Speech Lang Hear Res. 1999;42(4):972-989. doi:10.1044/jslhr.4204.972.
  19. Dunn J, Clare L. Learning face-name associations in early-stage dementia: comparing the effects of errorless learning and effortful processing. Neuropsychol Rehabil. 2007;17(6):735-754. doi:10.1080/09602010701218317.
  20. Duval J, Coyette F, Seron X. Rehabilitation of the central executive component of working memory: a re-organisation approach applied to a single case. Neuropsychol Rehabil. 2008;18(4):430-460. doi:10.1080/09602010701573950.
  21. Ehlhardt LA, Sohlberg MM, Glang A, Albin R. TEACH-M: a pilot study evaluating an instructional sequence for persons with impaired memory and executive functions. Brain Inj. 2005;19(8):569-583. doi:10.1080/02699050400013550.
  22. Eriksen CW. The flankers task and response competition: a useful tool for investigating a variety of cognitive problems. Visual Cognition. 1995;2(2-3):101-118. doi:10.1080/13506289508401726.
  23. Evald L. Prospective memory rehabilitation using smartphones in patients with TBI: what do participants report? Neuropsychol Rehabil. 2015;25(2):283-297. doi:10.1080/09602011.2014.970557.
  24. Franklin S, Buerk F, Howard D. Generalised improvement in speech production for a subject with reproduction conduction aphasia. Aphasiology. 2002;16(10-11):1087-1114. doi:10.1080/02687030244000491.
  25. Funk J, Finke K, Reinhart S, et al. Effects of feedback-based visual line-orientation discrimination training for visuospatial disorders after stroke. Neurorehabil Neural Repair. 2013;27(2):142-152. doi:10.1177/1545968312457826.
  26. Girelli L, Seron X. Rehabilitation of number processing and calculation skills. Aphasiology. 2001;15(7):695-712. doi:10.1080/02687040143000131.
  27. Girelli L, Delazer M, Semenza C, Denes G. The representation of arithmetical facts: evidence from two rehabilitation studies. Cortex. 1996;32(1):49-66. doi:10.1016/S0010-9452(96)80016-5.
  28. Hashimoto N, Frome A. The use of a modified semantic features analysis approach in aphasia. J Commun Disord. 2011;44(4):459-469. doi:10.1016/j.jcomdis.2011.02.004.
  29. Katz RC, Wertz RT. The efficacy of computer-provided reading treatment for chronic aphasic adults. J Speech Lang Hear Res. 1997;40(3):493-507. doi:10.1044/jslhr.4003.493.
  30. Kendall DL, Rosenbek JC, Heilman KM, et al. Phoneme-based rehabilitation of anomia in aphasia. Brain Lang. 2008;105(1):1-17. doi:10.1016/j.bandl.2007.11.007.
  31. Kerkhoff G. Rehabilitation of visuospatial cognition and visual exploration in neglect: a cross-over study. Restor Neurol Neurosci. 1998;12(1):27-40.
  32. Kiran S, Thompson CK. The role of semantic complexity in treatment of naming deficits: training semantic categories in fluent aphasia by controlling exemplar typicality. J Speech Lang Hear Res. 2003;46(3):608-622.
  33. Kiran S, Bassetto G. Evaluating the effectiveness of semantic-based treatment for naming deficits in aphasia: what works? Semin Speech Lang. 2008;29(1):71-82. doi:10.1055/s-2008-1061626.
  34. Kiran S, Johnson L. Semantic complexity in treatment of naming deficits in aphasia: evidence from well-defined categories. Am J Speech Lang Pathol. 2008;17(4):389-400. doi:10.1044/1058-0360(2008/06-0085).
  35. Kiran S, Viswanathan M. Effect of model-based treatment on oral reading abilities in severe alexia: a case study. J Med Speech Lang Pathol. 2008;16(1):43-59.
  36. Kiran S, Sandberg C, Abbot K. Treatment for lexical retrieval using abstract and concrete words in persons with aphasia: effect of complexity. Aphasiology. 2009;23(7):835-853. doi:10.1080/02687030802588866.
  37. Kiran S, Sandberg C, Sebastian R. Treatment of category generation and retrieval in aphasia: effect of typicality of category items. J Speech Lang Hear Res. 2011;54(4):1101-1117. doi:10.1044/1092-4388(2010/10-0117).
  38. Kiran S, Thompson CK, Hashimoto N. Training grapheme to phoneme conversion in patients with oral reading and naming deficits: a model-based approach. Aphasiology. 2001;15(9):855-876. doi:10.1080/02687040143000258.
  39. Kiran S. Training phoneme to grapheme conversion for patients with written and oral production deficits: a model-based approach. Aphasiology. 2005;19(1):53-76. doi:10.1080/02687030444000633.
  40. Klingberg T. Training and plasticity of working memory. Trends Cogn Sci. 2010;14(7):317-324. doi:10.1016/j.tics.2010.05.002.
  41. Lacey EH, Lott SN, Snider SF, Sperling A, Friedman RB. Multiple oral re-reading treatment for alexia: the parts may be greater than the whole. Neuropsychol Rehabil. 2010;20(4):601-623. doi:10.1080/09602011003710993.
  42. Li K, Robertson J, Ramos J, Gella S. Computer-based cognitive retraining for adults with chronic acquired brain injury: a pilot study. Occup Ther Health Care. 2013;27(4):333-344. doi:10.3109/07380577.2013.844877.
  43. Leonard C, Rochon E, Laird L. Treating naming impairments in aphasia: findings from a phonological components analysis treatment. Aphasiology. 2008;22(9):923-947. doi:10.1080/02687030701831474.
  44. Lloyd J, Riley GA, Powell TE. Errorless learning of novel routes through a virtual town in people with acquired brain injury. Neuropsychol Rehabil. 2009;19(1):98-109. doi:10.1080/09602010802117392.
  45. McGilton KS, Rivera TM, Dawson P. Can we help persons with dementia find their way in a new environment? Aging Ment Health. 2003;7(5):363-371. doi:10.1080/1360786031000150676.
  46. Martini L, Domahs F, Benke T, Delzaer M. Everyday numerical abilities in Alzheimer’s disease. J Int Neuropsychol Soc. 2003;9(6):871-878. doi:10.1017/S1355617703960073.
  47. McDonald A, Haslam C, Yates P, Gurr B, Leeder G, Sayers A. Google Calendar: a new memory aid to compensate for prospective memory deficits following acquired brain injury. Neuropsychol Rehabil. 2011;21(6):784-807. doi:10.1080/09602011.2011.598405.
  48. McAvinue L, O’Keeffe F, McMackin D, Robertson IH. Impaired sustained attention and error awareness in traumatic brain injury: implications for insight. Neuropsychol Rehabil. 2005;15(5):569-587. doi:10.1080/09602010443000119.
  49. Martin-Saez M, Deakins J, Winson R, Watson P, Wilson BA. A 10-year follow up of a paging service for people with memory and planning problems within a healthcare system: how do recent users differ from the original users? Neuropsychol Rehabil. 2011;21(6):769-783. doi:10.1080/09602011.2011.614378.
  50. Powell J, Letson S, Davidoff J, Valentine T, Greenwood R. Enhancement of face recognition learning in patients with brain injury using three cognitive training procedures. Neuropsychol Rehabil. 2008;18(2):182-203. doi:10.1080/09602010701419485.
  51. Rapp B. The relationship between treatment outcomes and the underlying cognitive deficit: evidence from the remediation of acquired dysgraphia. Aphasiology. 2005;19(10):994-1008. doi:10.1080/0268703054400029.
  52. Raymer AM, Kohen FP, Saffell D. Computerised training for impairments of word comprehension and retrieval in aphasia. Aphasiology. 2006;20(2-4):257-268. doi:10.1080/02687030500473312.
  53. Raymer AM, Ellsworth TA. Response to contrasting verb retrieval treatments: a case study. Aphasiology. 2002;16(10-11):1031-1045. doi:10.1080/026870401430000609.
  54. Renvall K, Laine M, Martin N. Treatment of anomia with contextual priming: exploration of a modified procedure with additional semantic and phonological tasks. Aphasiology. 2007;21(5):499-527. doi:10.1080/02687030701254248.
  55. Robson J, Marshall J, Chiat S, Pring T. Enhancing communication in jargon aphasia: a small group study of writing therapy. Int J Lang Commun Disord. 2001;36(4):471-488. doi:10.1080/13682820110089371.
  56. Rochon E, Leonard C, Burianova H, et al. Neural changes after phonological treatment for anomia: an fMRI study. Brain Lang. 2010;114(3):164-179. doi:10.1016/j.bandl.2010.05.005.
  57. Rose M, Douglas J. Treating a semantic word production deficit in aphasia with verbal and gesture methods. Aphasiology. 2008;22(1):20-41. doi:10.1080/02687030600742020.
  58. Salis C, Edwards S. Treatment of written verb and written sentence production in an individual with aphasia: a clinical study. Aphasiology. 2010;24(9):1051-1063. doi:10.1080/02687030903269648.
  59. Salis C. Short-term memory treatment: patterns of learning and generalisation to sentence comprehension in a person with aphasia. Neuropsychol Rehabil. 2012;22(3):428-448. doi:10.1080/09602011.2012.656460.
  60. Sandberg C, Kiran S. How justice can affect jury: training abstract words promotes generalisation to concrete words in patients with aphasia. Neuropsychol Rehabil. 2014;24(5):738-769. doi:10.1080/09602011.2014.899504.
  61. Stadie N, Schröder A, Postler J. Unambiguous generalization effects after treatment of non-canonical sentence production in German agrammatism. Brain Lang. 2008;104(3):211-229. doi:10.1016/j.bandl.2007.08.006.
  62. Stanczak L, Walters G, Caplan D. Typicality-based learning and generalisation in aphasia: two case studies of anomia treatment. Aphasiology. 2006;20(2-4):374-383. doi:10.1080/02687030600587631.
  63. Tessier C, Weill-Chounlamountry A, Michelot N, Pradat-Diehl P. Rehabilitation of word deafness due to auditory analysis disorder. Brain Inj. 2007;21(11):1165-1174. doi:10.1080/02699050701559186.
  64. Tsapkini K, Hills AE. Spelling intervention in post-stroke aphasia and primary progressive aphasia. Behav Neurol. 2013;26(1-2):55-66. doi:10.3233/BEN-2012-110240.
  65. Tzuriel D, Egozi G. Gender differences in spatial ability of young children: the effects of training and processing strategies. Child Dev. 2010;81(5):1417-1430. doi:10.1111/j.1467-8624.2010.01482.x.
  66. Vallat-Azouvi C, Pradat-Diehl P, Azouvi P. Rehabilitation of the central executive of working memory after severe traumatic brain injury: two single-case studies. Brain Inj. 2009;23(6):585-594. doi:10.1080/02699050902970711.
  67. Weinrich M, Boser KI, McCall D, Bishop V. Training agrammatic subjects on passive sentences: implications for syntactic deficit theories. Brain Lang. 2001;76(1):45-61. doi:10.1006/brin.2000.2421.
  68. Westerberg H, Jacobaeus H, Hirvikoski T, et al. Computerized working memory training after stroke—a pilot study. Brain Inj. 2007;21(1):21-29. doi:10.1080/02699050601148726.
  69. Whetstone T. The representation of arithmetic facts in memory: results from retraining a brain-damaged patient. Brain Cogn. 1998;36(3):290-309. doi:10.1006/brcg.1998.0997.
  70. Zaunmüller L, Domahs F, Dressel K, et al. Rehabilitation of arithmetic fact retrieval via extensive practice: a combined fMRI and behavioural case-study. Neuropsychol Rehabil. 2009;19(3):422-443. doi:10.1080/09602010802296378.

Constant Therapy by the numbers

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related studies

Featured research

Our latest study, published in Frontiers in Neurology, is the first large scale retrospective study of post-stroke rehabilitation practices that compares outcomes among patients using tablet-based therapy at home and those who complete the same therapy in a clinic.

Download the study overview

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Our technology: Empowering collective intelligence

  • The NeuroPerformance Engine™ (NPE) is the patented AI at the core of all our products.
  • Constantly monitors and analyzes the real-world evidence generated by user performance and progress.
  • Helps us discover new ways to improve individual exercises, fine-tune the sequence of therapies, and deliver personalized exercises at the right time.
  • Data insights advance the science of brain rehabilitation and health.

Awards

2014 Tie 50

Winner, Startup

2015 AARP Health Innovation@50+

Consumers' Choice 

2016 SBANE
New England

Innovation Award

2018 MassTLC

Tech for a Better Tomorrow

Timmy Awards

Finalist, Startup