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Assistive Technologies


The Best Assistive Technology for Dyslexics

WIRED

My daughter is part of the 15–20 percent of students and adults living with a language-based learning disability. According to the International Dyslexia Association, these individuals have some or all of the symptoms of dyslexia, including slow or inaccurate reading, poor spelling, poor writing, or mixing up similar words and numbers. Once we diagnosed her dyslexia, I understood she needed the help of assistive technology to learn at a rate on par with her classmates, but I wasn't sure where to start. In honor of Dyslexia Awareness Month this October, I reached out to several assistive technology experts to find out what technology they recommend for facilitating and improving reading, writing, spelling, and math. Here's what Jamie Martin, Assistive Technology Specialist at the New England Assistive Technology Center and Karen Janowski, Assistive & Educational Technology Consultant at EdTech Solutions and co-author of Inclusive Technology 365 recommend.


Exoskeleton research demonstrates the importance of training

#artificialintelligence

Exoskeleton devices work, researchers say, for a variety of uses such as speeding up our walking or making running easier. Yet they don't know what exactly makes exoskeletons effective. What is the benefit of customization, for example? And how much does simply getting used to the exoskeleton matter? Researchers in the Stanford Biomechatronics Laboratory at Stanford University examined these questions and found that training plays a remarkably significant role in how well exoskeletons provide assistance.


Back pain reducing exoskeleton for e-commerce workers

ZDNet

A Dutch exoskeleton company is launching an updated model of an innovative unpowered exoskeleton for workers. The new product from Laevo, called the Flex V3, is compelling for a couple of reasons, but the big one may be that it's attempting to solve well-known problems that have kept exoskeletons, once vaunted as a breakthrough technology, a primarily niche product. The Laevo device is a passive, unobtrusive exoskeleton designed to alleviate strain and adapt to every posture. By leaning against the chest pad, the Laevo transfers force from the rest of the body to the thighs. In general, exoskeletons have stumbled from a business perspective.


Scientists develop an exoskeleton to help amputees walk with much less effort

Daily Mail - Science & tech

An exoskeleton that lets amputees feel like they are'walking with two normal legs' has been developed by scientists using battery-powered electric motors. The powerful exoskeleton, which wraps around the wearer's waist and leg, was developed by a team of engineers at the University of Utah in Salt Lake City. It has been designed for above-the-knee amputees and uses battery-powered electric motors and embedded microprocessors to reduce walking effort. The 5.4lb frame is made of carbon-fibre material, plastic composites and aluminium and can walk for miles between charges, according to its creators. Those wearing it saw a 15.6 per cent reduction in their metabolic rate, equivalent to taking off a 26-pound backpack while out on a long walk, the team said.


White Sox fan catches home run ball with prosthetic leg

FOX News

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Why catch a fly ball with your hands when you can catch one with your leg? TikTok user Shannon Frandreis amazed her fellow fans when she caught a fly ball at a recent Chicago White Sox game with her prosthetic leg. The surrounding crowd stood up and cheered for Frandreis as she hoisted the leg up in the air, celebrating with a big smile on her face. Chicago White Sox's Yoan Moncada, left, celebrates with third base coach Joe McEwing after hitting a two-run home run during the eighth inning of a baseball game against the Detroit Tigers in Chicago, Saturday, Oct. 2, 2021.


MIT's new bionics center may usher in our cyborg future

#artificialintelligence

A new MIT research center promises to accelerate our journey to a future in which bionics help people everywhere overcome the challenges of disabilities -- and even enhance human potential. The future is near: Bionics replace or restore the function of missing or damaged body parts with electronic devices -- examples include leg exoskeletons and mind-controlled prosthetic arms. These devices can be life-changing, but many are still unique and experimental, meaning the only people to benefit from them are a handful of study participants. The faster we can advance bionics research, the sooner they'll be available to everyone who needs them. "We must continually strive towards a technological future in which disability is no longer a common life experience," MIT professor Hugh Herr, himself a double amputee, told MIT News.


Cleveland Clinic develops bionic arm that restores 'natural behaviors'

#artificialintelligence

Cleveland Clinic researchers have engineered a "first-of-its-kind bionic arm" for patients with upper-limb amputations that allows wearers to think, behave and function like a person without an amputation, according to new findings published in Science Robotics. The Cleveland Clinic-led international research team developed the bionic system that combines three important functions – intuitive motor control, touch and grip kinesthesia, the intuitive feeling of opening and closing the hand. Collaborators included University of Alberta and University of New Brunswick. "We modified a standard-of-care prosthetic with this complex bionic system which enables wearers to move their prosthetic arm more intuitively and feel sensations of touch and movement at the same time," said lead investigator Paul Marasco, PhD, associate professor in Cleveland Clinic Lerner Research Institute's Department of Biomedical Engineering. "These findings are an important step towards providing people with amputation with complete restoration of natural arm function."


Bionic arm combines intuitive motor control, touch and grip for the first time

Daily Mail - Science & tech

A bionic arm that combined intuitive motor control, touch and grip will allow amputees feel the sensation of feeling objects, its developers claim. This is the first prosthetic limb that is able to test all key functions of a hand at the same time, and uses a brain-computer interface to trigger the interaction. Lead investigator Professor Paul Marasco, of the Cleveland Clinic in Ohio, said test subjects felt one of their hands was moving, even though they didn't have a hand, and felt as if their fingers were touching things, even though they had no fingers. Putting touch, grip and motor control together, worked to trick the senses and brain of the wearer into thinking the prosthetic was a real human hand, Prof Marasco said. It links to limb nerves which send impulses from the patient's brains to the prosthetic when they want to use or move it, and the arm receives physical information from the environment through sensors, sending it back into the brain through nerves.


Neurorobotics for neurorehabilitation

Science

Advances in peripheral nervous system (PNS) interfacing present a promising alternative to traditional neuromodulation ([ 1 ][1]), particularly for individuals with upper-limb amputations ([ 2 ][2]–[ 7 ][3]). Implanted electrodes have been shown to diminish phantom limb pain (PLP) in such subjects and enable close-to-natural touch sensations. Individuals with peripheral neural stimulators are even able to control the amount of force exerted by a prosthesis and to discern among objects with different compliances and shapes with prosthesis ([ 2 ][2]–[ 5 ][4]). Successive studies have shown the long-term utility of these technologies ([ 6 ][5], [ 7 ][3]). Having successfully achieved functional stimulation and chronic biocompatibility through neural interfaces, the focus of neuromodulation research is shifting toward achieving optimal design and policy of use ([ 8 ][6]). There is great variety in electrode geometries, stimulating contact numbers, and placement within the nervous system (see the figure) as well as in possible stimulation protocols. Optimization will not be achieved with brute force but requires the development of computational models ([ 9 ][7], [ 10 ][8]) capable of exploiting the knowledge that has been accumulated on this topic. Until recently, most research has focused on hand amputees, neglecting the clinical reality that four out of five amputees have lower-limb loss. Subjects with lower-limb amputation frequently do not engage fully in everyday activities because they are afraid of falls and do not perceive the prosthesis as part of their body (low “embodiment”). Such individuals often report poor satisfaction with their prostheses, citing the prosthesis as an excessive weight, despite prosthetic limbs typically being less than half the weight of a natural limb ([ 11 ][9]). They also tend to have reduced mobility ([ 12 ][10]), which can induce a sedentary lifestyle that promotes disease development and hinders reinsertion into society. PLP is also common and is poorly managed with current medications ([ 13 ][11]). Additionally, those with lower-limb amputations face substantially higher metabolic costs while walking, resulting in an increased risk of heart attack compared with the general population ([ 14 ][12]). We have pioneered a human-machine system that translates prosthetic sensors' readouts into “language” understandable by the nervous system, using a detailed computational model ([ 9 ][7], [ 10 ][8]) that indicates an optimal number of implants for the targeted nerve. Compared with traditional frequency variation, the model favors current amplitude modulation, for increasing efficiency of mapping and closed-loop stimulation ([ 15 ][13]). Placement of the cable connecting implants to the stimulator is a longstanding problem and a frequent cause of failure in implantable technologies during clinical testing ([ 7 ][3], [ 8 ][6]). We addressed this issue during surgical preparation by implementing a release loop and stabilization within the fascia tissue graft with cables embedded in the middle ([ 14 ][12]). We developed a “sensing leg,” for lower-limb amputees, by connecting sensors from the prosthetic knee and under the foot to the residual PNS (see the figure). An effective connection was achieved by equipping a microprocessor-controlled prosthesis with a purposely developed sensorized insole. An external controller that communicates wirelessly with the “sensorized prosthesis” proportionally transduces the readout of the insole and knee sensors into stimulation parameters. The stimulator then injects the current into the intraneural electrodes, eliciting sensations from the missing lower limb. The whole process ran at a delay unperceivable to the user, enabling real-time neuromodulation dependent on leg status. This intervention enabled recovery of rich leg and foot perceptions (such as touch, proprioception, and both simultaneously). Users were able to recognize when the prosthetic leg—physically disconnected from their body and communicating wirelessly with the implants—was touched over different foot positions, flexed, or both. Users were also able to avoid a substantially higher number of stumbles when walking over obstacles, while wearing glasses that blind their lower field of vision, than when not exploiting the restored feedback. Climbing stairs is often a challenge for above-knee amputees, resulting in very slow motion and considerable fatigue. When neuromodulation restored limb perception, their mobility substantially increased ([ 15 ][13]). After these laboratory tests, volunteers stepped outside into a more natural environment. Because of the fully portable neuromodulating system, their confidence was increased, and subjects were able to walk with increased speed over what would normally be challenging sandy terrain. At the same time, volunteers' metabolic consumption was diminished when sensory neurofeedback was switched on. The decreased energy expenditure when using neuromodulation could potentially limit cardiovascular system fatigue—a tremendously important health benefit for lower-limb amputees ([ 14 ][12]). When the implantable system was used in “neuro-pacemaker modality”—stimulating the nerve without connection to the prosthesis—a reduction in PLP was observed. Through precise somatotopic stimulation, we have evoked pleasant, close-to-natural sensations within regions of referred pain. By contrast, commercial stimulation devices mainly deliver prefixed and often ineffective patterns of stimuli, which do not elicit physiologically plausible sensations and fail to deliver effective relief ([ 16 ][14]), and spinal cord stimulators involve the induction of paresthesia (an uncomfortable tingling), which does not always completely relieve the pain ([ 17 ][15]). Meanwhile, neurostimulators that directly target the peripheral nerve deliver either nonselective stimulation or induce an analgesic nerve block, both of which have considerable drawbacks ([ 18 ][16]). Our neuromodulation pain treatment represents a real advance with respect to existing treatments, in that we restore naturalistic percepts, revitalizing the physiological pathway for sensations. Beside the imminent pain relief, this potentially induces beneficial long-term neuroplastic changes at the central nervous system (CNS) level, offering not only an analgesic but also a “curative” effect. As a consequence of the restoration of physiologically plausible sensations, subjects experienced (“embodied”) the prosthesis similar to a real limb. Embodiment is typically measured in “nonfunctional” scenarios [such as rubber-hand experiments ([ 19 ][17])]. We were able to measure an objective functional embodiment ([ 20 ][18]) increase during our experiments with the bionic leg, with and without feedback ([ 15 ][13]). Increased neural embodiment decreased weight perception ([ 11 ][9])—a subjective percept influenced by cognitive processes. Brain cognitive load, measured with electroencephalography, also decreased while walking with the neuroprosthesis and performing a dual task ([ 15 ][13]). ![Figure][19] Different neurotechnologies for the peripheral nervous system (PNS) interfacing Various types of neural electrodes are utilized in individuals with upper- and lower-limb amputation to take input from prosthesis sensors and transduce it into electrical stimulation—restoring sensation from missing appendages. GRAPHIC: C. BICKEL/ SCIENCE BASED ON S. RASPOPOVIC Neuromodulation triggered by a robotic device influences sensorimotor strategies employed by users, by means of its integration into their “traditional” nervous system. To better understand underlying mechanisms, we measured gait features of leg amputees during motor tasks of different difficulty while using the neuroprosthesis. They performed an easy task (walking over ground) and a challenging task (ascending and descending stairs) while gait and neurostimulating parameters were collected. The neuroprosthesis reshaped subjects' legs' kinematics toward a more physiological gait owing to sensorimotor strategies that allowed users to intuitively exploit various features of the neural code during different tasks ([ 21 ][20]). These strategies included different temporal order, or spatial usage of stimulation channels, resulting in simple but robust intuitively integrated neural codes for different motor behaviors. In a hypothetical scenario, which required a leg amputee to simulate driving a conventional car, we demonstrated a finer pressure estimation from the prosthesis, suggesting that even a simple neural code could effectively improve wearable neuromodulating devices. These studies not only provided clear evidence of the benefit of neuromodulation for lower-limb amputees but also provided insights into fundamental mechanisms of supraspinal integration of the restored sensory modalities. Even with only a limited restoration of sensations from foot and knee, the CNS was able to successfully integrate and exploit this information. Analogous findings were observed in animals that compensated for lack of a single sensory modality through supraspinal structures ([ 22 ][21]). The health benefits achievable from neuromodulation are of paramount importance to millions of impaired individuals. Because the economic cost of such technologies remains considerable, it is important to emphasize the accompanying benefits, which could eliminate the need for treatments related to pain or cardiovascular problems ([ 1 ][1]). Together with pioneering results in neuromodulating treatment for neuropathy, the described research presents a conceptually new framework for neuroprosthetic device design, implementation, and testing. This iterative framework consists of (i) developing a deep understanding of the problem through models and experiments, (ii) influencing the device design, and (iii) a meticulously planned clinical testing phase. Multifaceted validation of experiments—including functional, emotional, and cognitive outcomes—feeds back to increase our knowledge and further optimize design. Model-based, deep understanding of the effects of neuromodulation could benefit future projects in the emerging field of bioelectronic medicine ([ 23 ][22], [ 24 ][23]). GRAND PRIZE WINNER Stanisa Raspopovic Stanisa Raspopovic received undergraduate degrees from the University of Pisa and a PhD from Scuola Superiore Sant'Anna, Italy. After completing his postdoctoral fellowship at EPFL, he started his laboratory in the Department of Health Science and Technology at ETH Zürich in 2018. His research focuses on deep understanding of nervous system interaction with electric field through computational modeling, design of sensory neuroprostheses, and bioelectronics solutions and the investigation of human interaction with these. FINALIST Weijian Yang Weijian Yang received his undergraduate degree from Peking University and a PhD from the University of California, Berkeley. After completing his postdoctoral fellowship at Columbia University, he started his laboratory in the Department of Electrical and Computer Engineering at the University of California, Davis in 2017. His research aims to develop advanced optical methods and neurotechnologies to interrogate and modulate brain activity, with a goal to understand how neural circuits organize and function and how behaviors emerge from neuronal activity. 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{openurl}?query=rft.jtitle%253DN.%2BEngl.%2BJ.%2BMed.%26rft.volume%253D382%26rft.spage%253D1732%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [40]: #xref-ref-7-1 "View reference 7 in text" [41]: {openurl}?query=rft.jtitle%253DAnn.%2BNeurol.%26rft.volume%253D85%26rft.spage%253D137%26rft_id%253Dinfo%253Adoi%252F10.1002%252Fana.25384%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [42]: /lookup/external-ref?access_num=10.1002/ana.25384&link_type=DOI [43]: #xref-ref-8-1 "View reference 8 in text" [44]: {openurl}?query=rft.jtitle%253DNat.%2BMater.%26rft.volume%253D20%26rft.spage%253D925%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [45]: #xref-ref-9-1 "View reference 9 in text" [46]: {openurl}?query=rft.jtitle%253DProc.%2BIEEE%26rft.volume%253D105%26rft.spage%253D34%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [47]: #xref-ref-10-1 "View reference 10 in text" [48]: {openurl}?query=rft.jtitle%253DJ.%2BNeuroeng.%2BRehabil.%26rft.volume%253D17%26rft.spage%253D24%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [49]: 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{openurl}?query=rft.jtitle%253DGait%2B%2526%2Bposture%26rft.stitle%253DGait%2BPosture%26rft.aulast%253DNolan%26rft.auinit1%253DL.%26rft.volume%253D17%26rft.issue%253D2%26rft.spage%253D142%26rft.epage%253D151%26rft.atitle%253DAdjustments%2Bin%2Bgait%2Bsymmetry%2Bwith%2Bwalking%2Bspeed%2Bin%2Btrans-femoral%2Band%2Btrans-tibial%2Bamputees.%26rft_id%253Dinfo%253Adoi%252F10.1016%252FS0966-6362%252802%252900066-8%26rft_id%253Dinfo%253Apmid%252F12633775%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [53]: /lookup/external-ref?access_num=10.1016/S0966-6362(02)00066-8&link_type=DOI [54]: /lookup/external-ref?access_num=12633775&link_type=MED&atom=%2Fsci%2F373%2F6555%2F634.atom [55]: /lookup/external-ref?access_num=000181734500008&link_type=ISI [56]: #xref-ref-13-1 "View reference 13 in text" [57]: {openurl}?query=rft.jtitle%253DLancet.%2BNeurology%26rft.stitle%253DLancet%2BNeurol%26rft.aulast%253DFlor%26rft.auinit1%253DH.%26rft.volume%253D1%26rft.issue%253D3%26rft.spage%253D182%26rft.epage%253D189%26rft.atitle%253DPhantom-limb%2Bpain%253A%2Bcharacteristics%252C%2Bcauses%252C%2Band%2Btreatment.%26rft_id%253Dinfo%253Adoi%252F10.1016%252FS1474-4422%252802%252900074-1%26rft_id%253Dinfo%253Apmid%252F12849487%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [58]: /lookup/external-ref?access_num=10.1016/S1474-4422(02)00074-1&link_type=DOI [59]: /lookup/external-ref?access_num=12849487&link_type=MED&atom=%2Fsci%2F373%2F6555%2F634.atom [60]: /lookup/external-ref?access_num=000177695100020&link_type=ISI [61]: #xref-ref-14-1 "View reference 14 in text" [62]: {openurl}?query=rft.jtitle%253DNat.%2BMed.%26rft.volume%253D25%26rft.spage%253D1356%26rft_id%253Dinfo%253Adoi%252F10.1038%252Fs41591-019-0567-3%26rft_id%253Dinfo%253Apmid%252F31501600%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [63]: /lookup/external-ref?access_num=10.1038/s41591-019-0567-3&link_type=DOI [64]: /lookup/external-ref?access_num=31501600&link_type=MED&atom=%2Fsci%2F373%2F6555%2F634.atom [65]: #xref-ref-15-1 "View reference 15 in text" [66]: {openurl}?query=rft.jtitle%253DScience%2BTranslational%2BMedicine%26rft.stitle%253DSci%2BTransl%2BMed%26rft.aulast%253DPetrini%26rft.auinit1%253DF.%2BM.%26rft.volume%253D11%26rft.issue%253D512%26rft.spage%253Deaav8939%26rft.epage%253Deaav8939%26rft.atitle%253DEnhancing%2Bfunctional%2Babilities%2Band%2Bcognitive%2Bintegration%2Bof%2Bthe%2Blower%2Blimb%2Bprosthesis%26rft_id%253Dinfo%253Adoi%252F10.1126%252Fscitranslmed.aav8939%26rft_id%253Dinfo%253Apmid%252F31578244%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [67]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MTE6InNjaXRyYW5zbWVkIjtzOjU6InJlc2lkIjtzOjE1OiIxMS81MTIvZWFhdjg5MzkiO3M6NDoiYXRvbSI7czoyMjoiL3NjaS8zNzMvNjU1NS82MzQuYXRvbSI7fXM6ODoiZnJhZ21lbnQiO3M6MDoiIjt9 [68]: 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{openurl}?query=rft.jtitle%253DSurgical%2Bneurology%26rft.stitle%253DSurg%2BNeurol%26rft.aulast%253DKumar%26rft.auinit1%253DK.%26rft.volume%253D50%26rft.issue%253D2%26rft.spage%253D110%26rft.epage%253D120%26rft.atitle%253DEpidural%2Bspinal%2Bcord%2Bstimulation%2Bfor%2Btreatment%2Bof%2Bchronic%2Bpain--some%2Bpredictors%2Bof%2Bsuccess.%2BA%2B15-year%2Bexperience.%26rft_id%253Dinfo%253Adoi%252F10.1016%252FS0090-3019%252898%252900012-3%26rft_id%253Dinfo%253Apmid%252F9701116%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [72]: /lookup/external-ref?access_num=10.1016/S0090-3019(98)00012-3&link_type=DOI [73]: /lookup/external-ref?access_num=9701116&link_type=MED&atom=%2Fsci%2F373%2F6555%2F634.atom [74]: /lookup/external-ref?access_num=000075183100017&link_type=ISI [75]: #xref-ref-18-1 "View reference 18 in text" [76]: {openurl}?query=rft.jtitle%253DJ.%2BNeural%2BEng.%26rft.volume%253D15%26rft.spage%253D031002%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [77]: #xref-ref-19-1 "View reference 19 in text" [78]: {openurl}?query=rft.jtitle%253DNature%26rft.stitle%253DNature%26rft.aulast%253DBotvinick%26rft.auinit1%253DM.%26rft.volume%253D391%26rft.issue%253D6669%26rft.spage%253D756%26rft.epage%253D756%26rft.atitle%253DRubber%2Bhands%2B%2527feel%2527%2Btouch%2Bthat%2Beyes%2Bsee.%26rft_id%253Dinfo%253Adoi%252F10.1038%252F35784%26rft_id%253Dinfo%253Apmid%252F9486643%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [79]: /lookup/external-ref?access_num=10.1038/35784&link_type=DOI [80]: /lookup/external-ref?access_num=9486643&link_type=MED&atom=%2Fsci%2F373%2F6555%2F634.atom [81]: /lookup/external-ref?access_num=000072089500037&link_type=ISI [82]: #xref-ref-20-1 "View reference 20 in text" [83]: {openurl}?query=rft.jtitle%253DJ.%2BNeurol.%2BNeurosurg.%2BPsychiatry%26rft_id%253Dinfo%253Adoi%252F10.1136%252Fjnnp-2018-318570%26rft_id%253Dinfo%253Apmid%252F30100550%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [84]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiRlVMTCI7czoxMToiam91cm5hbENvZGUiO3M6NDoiam5ucCI7czo1OiJyZXNpZCI7czo4OiI5MC83LzgzMyI7czo0OiJhdG9tIjtzOjIyOiIvc2NpLzM3My82NTU1LzYzNC5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30= [85]: #xref-ref-21-1 "View reference 21 in text" [86]: 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How to use text-to-speech on TikTok

Mashable

TikTok's text-to-speech feature allows creators to put text over their videos and have a Siri-like voice read it out loud. It's a helpful way to annotate your videos to help describe what's happening, add context, or to serve whatever purpose you see fit. There's also no rule saying you can't use it just to make the text-to-speech voice say silly things. Here's how you can easily add text-to-speech to your TikTok videos. You can cancel it, edit the text, or adjust the duration of the text just by tapping the text again. Once you're happy with your video, just click "Next," apply whatever hashtags you want, and post!