Maryam Esfandiari shows how the device works and Vasileios Papapanagiotou describes how the data generated are filtered and fitted to the CFI curve. Per S&#246;dersten describes the research on which the clinical intervention relies and Cecilia Bergh discusses its use in the clinic. The work is supported by Mando Group AB, the European Community's ICT Programme SPLENDID (610746) and the European Community's Health, demographic change and well-being Programme (727688).

All work on experimental subjects and patients has been approved by the Central Ethical Review Board of Stockholm, Sweden.
1. Control of Eating Rate and Food Intake by Visual Feedback
<ol>
	<li>Download the device application.</li>
	<li>Turn on the scale by pressing the red button on the bottom of the scale (Figure 1).</li>
	<li>Open the application and select a meal by pressing Control to eat without visual feedback or by pressing Training to eat with visual feedback (Figure 2).</li>
	<li>Connect the scale to the smartphone by selecting one of the scales found and pressing CONNECT (Figure 3).</li>
	<li>Place a plate on the scale. Press Done to continue (Figure 4).</li>
	<li>Put food on the plate (0%).
	<ol>
		<li>Put more food on the plate (72%).</li>
		<li>Press Start when ready to eat (100%) (Figure 5).</li>
	</ol>
	</li>
	<li>Adapt rate of eating to the dashed blue reference curve (Figure 6).</li>
	<li>Rate feeling of fullness when the rating scale appears on the screen. Adapt rating of fullness to the s-shaped dashed purple reference curve. Press Done to continue eating (Figure 7).</li>
	<li>Slow down if eating too quickly (Figure 8).</li>
	<li>With no food left on plate, press No when finished eating (Figure 9).</li>
	<li>As the meal duration is shown when meal is finished, press Done to exit (Figure 10).</li>
</ol>

<ol>
	<li>Zandian, M., Ioakimidis, I., Bergh, C., Brodin, U., S&#246;dersten, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Decelerated+and+linear+eaters:+Effect+of+eating+rate+on+food+intake+and+satiety.">Decelerated and linear eaters: Effect of eating rate on food intake and satiety.</a> Physiol. Behav. 96, 270-275 (2009).</li><li>. Elements of the Theory of Computation Available from: <a target="_blank" href="https://dl.acm.org/citation.cfm?id=549820">https://dl.acm.org/citation.cfm?id=549820</a> (1997)</li><li>Lieberman, D. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Evolution of the Human Head. , (2011).</li><li>Ungar, P. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Evolution's Bite: A Story of Teeth, Diet, and Human Origins. , (2017).</li><li>Al-Khudairy, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=physical+activity+and+behavioural+interventions+for+the+treatment+of+overweight+or+obese+adolescents+aged+12+to+17+years.">physical activity and behavioural interventions for the treatment of overweight or obese adolescents aged 12 to 17 years.</a> Cochrane Database Syst. Rev. 6, CD012691 (2017).</li><li>Zandian, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Children+eat+their+school+lunch+too+quickly:+an+exploratory+study+of+the+effect+on+food+intake.">Children eat their school lunch too quickly: an exploratory study of the effect on food intake.</a> BMC Public Health. 12, (2012).</li><li>Zandian, M., Ioakimidis, I., Bergh, C., Leon, M., S&#246;dersten, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+sex+difference+in+the+response+to+fasting.">A sex difference in the response to fasting.</a> Physiol. Behav. 103, 530-534 (2011).</li><li>Xu, B., Xie, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neurotrophic+factor+control+of+satiety+and+body+weight.">Neurotrophic factor control of satiety and body weight.</a> Nat. Rev. Neurosci. 17, 282-292 (2016).</li><li>GBD 2015 Obesity Collaborators. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Health+effects+of+overweight+and+obesity+in+195+countries+over+25+years.">Health effects of overweight and obesity in 195 countries over 25 years.</a> N. Engl. J. Med. , 13-27 (2017).</li><li>Morley, J. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diabetes:+the+diabetic+brain.">Diabetes: the diabetic brain.</a> Nat. Rev. Endocrinol. 13, 570-571 (2017).</li><li>Aslibekyan, S., Garvey, W. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Obesity:+Obesity+and+cardiometabolic+disease+-+more+than+meets+the+eye.">Obesity: Obesity and cardiometabolic disease - more than meets the eye.</a> Nat. Rev. Endocrinol. 13, 566-568 (2017).</li><li>S&#246;dersten, P., Bergh, C., Zandian, I., Ioakimidis, <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Obesity+and+the+brain.">Obesity and the brain.</a> Med. Hypotheses. 77, 371-373 (2011).</li><li>Hendricks, A. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rare+variant+analysis+of+human+and+rodent+obesity+genes+in+individuals+with+severe+childhood+obesity.">Rare variant analysis of human and rodent obesity genes in individuals with severe childhood obesity.</a> Sci. Rep. 7, 4394 (2017).</li><li>Ammar, A. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=NPY-leptin:+opposing+effects+on+appetitive+and+consummatory+ingestive+behavior+and+sexual+behavior.">NPY-leptin: opposing effects on appetitive and consummatory ingestive behavior and sexual behavior.</a> Am. J. Physiol. Regul. Integr. Comp. Physiol. 278, R1627-R1633 (2000).</li><li>Nerg&#229;rdh, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neuropeptide+Y+facilitates+activity-based-anorexia.">Neuropeptide Y facilitates activity-based-anorexia.</a> Psychoneuroendocrinology. 32, 493-502 (2007).</li><li>Chen, Y., Lin, Y. -. C., Kuo, T. -. W., Knight, Z. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sensory+detection+of+food+rapidly+modulates+arcuate+feeding+circuits.">Sensory detection of food rapidly modulates arcuate feeding circuits.</a> Cell. 160, 829-841 (2015).</li><li>Burnett, C. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hunger-driven+motivational+state+competition.">Hunger-driven motivational state competition.</a> Neuron. 92, 187-201 (2016).</li><li>Nerg&#229;rdh, R., Nerg&#229;rdh, R., Bergh, C., Zandian, M., Scheurink, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Behavioral+neuroendocrinology+and+treatment+of+anorexia+nervosa.">Behavioral neuroendocrinology and treatment of anorexia nervosa.</a> Front. Neuroendocrinol. 29, 445-462 (2008).</li><li>S&#246;dersten, P., Nusbaum, M. P., Blitz, D. M., Marder, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Functional+consequences+of+neuropeptide+and+small-molecule+co-transmission.">Functional consequences of neuropeptide and small-molecule co-transmission.</a> Nat. Rev. Neurosci. 18, 389-403 (2017).</li><li>Mead, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Drug+interventions+for+the+treatment+of+obesity+in+children+and+adolescents.">Drug interventions for the treatment of obesity in children and adolescents.</a> Cochrane Database Syst. Rev. 11, CD012436 (2016).</li><li>Himmerich, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Olanzapine+treatment+for+patients+with+anorexia+nervosa.">Olanzapine treatment for patients with anorexia nervosa.</a> Can. J. Psychiatry. 62, 506-507 (2017).</li><li>Mayer, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genetic,+traumatic+and+environmental+factors+in+the+etiology+of+obesity.">Genetic, traumatic and environmental factors in the etiology of obesity.</a> Physiol. Rev. 33, 472-508 (1953).</li><li>Periwal, V., Chow, C. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Patterns+in+food+intake+correlate+with+body+mass+index.">Patterns in food intake correlate with body mass index.</a> Am. J. Physiol. Endocrinol. Metab. 291, E929-E936 (2006).</li><li>Bergh, C., Leon, M., Brodin, U., Zandian, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cognitive+behavior+therapy+for+eating+disorders+versus+normalization+of+eating+behavior.">Cognitive behavior therapy for eating disorders versus normalization of eating behavior.</a> Physiol. Behav. 174, 178-190 (2017).</li><li>Freeman, C. P. L., Barry, F., Dunkeld-Turnbull, J., Henderson, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Controlled+trial+of+psychotherapy+for+bulimia+nervosa.">Controlled trial of psychotherapy for bulimia nervosa.</a> Br. Med. J. Clin. Res. Ed. 296, 521 (1988).</li><li>S&#246;dersten, P., Bergh, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effective+treatment+of+eating+disorders:+results+at+multiple+sites.">Effective treatment of eating disorders: results at multiple sites.</a> Behav. Neurosci. 127, 878-889 (2013).</li><li>Yamagishi, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Impact+of+speed-eating+habit+on+subsequent+body+mass+index+and+blood+pressure+among+schoolchildren+-+The+Ibaraki+Children's+Cohort+Study+(IBACHIL).">Impact of speed-eating habit on subsequent body mass index and blood pressure among schoolchildren - The Ibaraki Children's Cohort Study (IBACHIL).</a> Circ. J. Off. J. Jpn. Circ. Soc. , (2017).</li><li>Ford, A. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Treatment+of+childhood+obesity+by+retraining+eating+behaviour:+randomised+controlled+trial.">Treatment of childhood obesity by retraining eating behaviour: randomised controlled trial.</a> BMJ. 340, b5388 (2010).</li><li>Jordan, H. A., Wieland, W. F., Zebley, S. P., Stellar, E., Stunkard, A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Direct+measurement+of+food+intake+in+man:+a+method+for+the+objectiive+study+of+eating+behavior.">Direct measurement of food intake in man: a method for the objectiive study of eating behavior.</a> Psychosom. Med. 28, 836-842 (1966).</li><li>Meyer, J. -. E., Pudel, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experimental+studies+on+food-intake+in+obese+and+normal+weight+subjects.">Experimental studies on food-intake in obese and normal weight subjects.</a> J. Psychosom. Res. 16, 305-308 (1972).</li><li>Kissileff, H. R., Klingsberg, G., Itallie, T. B. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Universal+eating+monitor+for+continuous+recording+of+solid+or+liquid+consumption+in+man.">Universal eating monitor for continuous recording of solid or liquid consumption in man.</a> Am. J. Physiol. - Regul. Integr. Comp. Physiol. 238, R14-R22 (1980).</li><li>Zandian, M., Ioakimidis, I., Bergh, C., S&#246;dersten, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Linear+eaters+turned+decelerated:+reduction+of+a+risk+for+disordered+eating?.">Linear eaters turned decelerated: reduction of a risk for disordered eating?.</a> Physiol. Behav. 96, 518-521 (2009).</li><li>Zandian, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Control+of+Body+Weight+by+Eating+Behavior+in+Children.">Control of Body Weight by Eating Behavior in Children.</a> Front. Pediatr. 3, (2015).</li><li>Bergh, C., Brodin, U., Lindberg, G., S&#246;dersten, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Randomized+controlled+trial+of+a+treatment+for+anorexia+and+bulimia+nervosa.">Randomized controlled trial of a treatment for anorexia and bulimia nervosa.</a> Proc. Natl. Acad. Sci. 99, 9486-9491 (2002).</li><li>Ioakimidis, I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Description+of+chewing+and+food+intake+over+the+course+of+a+meal.">Description of chewing and food intake over the course of a meal.</a> Physiol. Behav. 104, 761-769 (2011).</li></ol>

Our research is carried out at the Karolinska Institute, where S&#246;dersten is a professor. The research is translated clinically by Mando Group AB, a company started by S&#246;dersten and Bergh, who have 47.5% of the stock each. Professor Michael Leon of the University of California at Irvine has 5%. Mando Group AB contracts with the County Council of Stockholm every fifth year to treat patients with eating disorders. Mando Groups AB signed its first contract in 1997 with the County Council of Stockholm and, since then, its treatment is one standard of care offered to the citizens of Stockholm. This arrangement is the same as when the County Council of Stockholm contracts with its own clinics to treat patients with all kinds of disease, including eating disorders. That is to say, the County Council of Stockholm provides eating disorders services to the citizens of Stockholm both through a clinic of its own and through Mando Group AB. There is a third provider of care for patients with eating disorders in Stockholm, which is a private clinic. All health care in Sweden is funded through the tax system, private pay is extremely uncommon. However, patients can pay privately for treatment by Mando Group AB and patients from Australia have done that because insurers in Australia have denied reimbursement. It should be added, firstly, that Mando Group AB is in compliance with the recommendation of the International Committee of Medical Journal Editors on &#8220;Author Responsibilities-Conflicts of Interest&#8221; http://www.icmje.org/recommendations/browse/roles-and-responsibilities/author-responsibilities--conflicts-of-interest.html. Secondly, it should also be added that all profit that Mando Group AB has made has been re-invested in research and development and that there have been no dividends to stock owners. This policy will not be changed. All of the above is declared in all manuscript submissions and so far, journals have judged it necessary to publish only some of the details. It seems, however, that the potential ethical problem when scientists translate research findings into the clinic in a company is not unlike that which arises when any scientist, in an academic setting, is developing a theory and needs further economic funding for her/his work and may receive recognition and financial benefits for the work. The incentive is, in part, economic in this case as well and the ethical &#8220;problem&#8221; is similar in both cases. However, the more important incentive is the improvement of the treatment of patients with eating disorders. Medical institutes, including the Karolinska Institute, encourage the translation of research into the clinic in companies that aim to generate financial profits to be used for research and development (see: http://ki.se.proxy.kib.ki.se/sites/default/files/summary_strategy2018.pdf).

While the method described here is a major intervention in our treatment of patients with problems of body weight, the treatment has additional interventions, which have been described before, including criteria for admission and remission34 and outcome at three months intervals in each of 1428 patients26. The device, not these additional interventions, is the focus of the present report.
The Control mode of the device is used to record eating behavior in healthy subjects and in under- and overweight patients. The Training mode is subsequently used to change eating behavior for experimental or clinical purposes. Using visual feedback in the treatment of anorexic patients, 100% as indicated on the computer screen, is the amount of food the patient should eat determined individually on the basis of three preliminary tests in the Control mode. 100% is a small amount of food in an anorexic patient, but more food than s/he ate in the three preliminary tests. An anorexic patient pratices eating progressively more food, and s/he is asked to add food until 100% is indicated on the screen. The shape of the dashed blue reference curve, which remains the same over the course of treatment, is based on the finding that normal weight healthy people eat at a progessively decreasing rate, i.e., in a decelerated manner1. The dashed purple reference curve for the feeling of fullness is based on the finding that the cumulative satiety curve is best fitted to a sigmoid curve1. There are no numbers on the axes. The treatment continues until the patient is able to eat about 300-350 g of food in about 10-15 min without a reference curve. These data were obtained from normal weight, healthy subjects. Both under- and overweight patients have a choice between three dishes of ordinary Swedish food in clinical pratice and they are offered water to drink. Experimental manipulation of eating behavior is done in the same manner in healthy subjects1,6,7,32,33. Because re-establishing the normal feeling of fullness using the visual feedback provided by a reference curve is done in the same manner it is not discussed here. Clinically, however, this is an important intervention as anorexic patients rate the feeling of fullness much higher than do healthy subjects.
While patients follow the visual feedback when eating in treatment, they are allowed to add food to the plate during the meal when they eat without feedback. Food additions and other events, including pressure exterted on the plate during sectioning of the food using forks and knives, affect the recording by the device creating artifacts and errors that were previously dealt with manually as described in35. The data generated from eating using the device is collected in a custom made database, from which the clinician can retrieve the results for providing patients with feeback on how treatment progresses and the researcher can use for analysing experimental results.
Anorexic patients eat only little food at a slow rate34. Interestingly, however, they are able to consume normal sized meals even at very low BMI18. For example, the patient reported was able to eat 300 g very early in treatment and long before normalization of her BMI and a mere three days after eating in a disordered manner, i.e., consuming only little food at an accelerating rate. Anorexic patients who start eating at an extremely low rate are likely to increase the rate of eating over the course of the initial meals, as did three of the patients reported here. When patients approach remission, however, the inverse relationship among the rate of deceleration and the initial rate of eating emerges1. Several hundred patients with eating disorders have been treated to remission and the protocol has proven user friendly with no adverse side effects26. Severely obese patients have been similarly treated to lose weight, albeit not to a normal weight28,33. At present there is no method that normalizes the body weight of severely overweight patients.
A limitation of the method is that subjects are likely affected by the device even in the absence of visual feedback. That hypothesis can be tested by comparing data obtained with the device with data obtained from video-recorded meals. Paradoxically, the same limitation may be an advantage in treatment, which aims at normalizing food intake.
While the present method has long been used to record eating behavior, the addition of visual feedback for experimental and clinical purposes has not been used outside our research and clinic. For clinicians aiming at restoring the eating behavior of the patients and for scientists interested in using eating behavior as an experimental variable, the device offers a method. The analysis of the results can now be automated using the present algorithm for computing the CFI curve, alleviating the need for time-consuming manual processing. This makes monitoring and analysis of eating behavior in large groups of subjects possible.
The effectiveness of the algortihm will be further improved. At present it is based on estimations of deviations from true values of bites as dissociated from artifacts.
The device will be used among children to prevent problems of body weight in adulthood. Most of the hardware and software discussed in this report are ready for such large scale use. Possible improvements, including optimizing the visual design of feedback on the screen of the device and expanding the CFG with additional kinds of in-meal actions and the analysis of partially completed meals, must await the outcome of the intended large scale use.

The device presented here is used to restore the body weight and the health of under- and overweight patients by controlling the rate of eating and the intake of food via visual feedback provided on a computer screen during the meal. It consists of a custom made electronic scale and a computer, e.g., a smartphone. An app allows a subject to connect the smartphone to the scale via Bluetooth. Once the smartphone is connected to the scale, the subject puts a plate on the scale and food on the plate and starts eating. At regular intervals, a rating scale appears on the screen and the subject is asked to rate her/his feeling of fullness. The rating scale can be disconnected, depending upon the aim of the experiment or the clinical intervention. For experimental and clinical purposes a reference curve for eating rate and a reference curve for the feeling of fullness are displayed on the screen of the smartphone. The subject can adapt to the reference curves because her/his rate of eating and ratings of fullness appear on the screen during the meal.
The device records the decrease of the weight of the plate as food is consumed and the ratings of fullness over the course of the meal and stores the recordings. The weight loss data are used to yield a quadratic model of the cumulative food intake (CFI) curve: y=kx2+lx, where y=amount of food consumed, k=change in the rate of eating over the course of the meal and l=initial rate of eating1. The CFI curve is based on modelling the following three actions during the meal: bite, food addition, and artifact (weight changes unrelated to food consumption). These actions are mapped on non-terminal symbols of a context-free grammar (CFG)2. The recording, after pre-processing, is partitioned into time intervals corresponding to weight changes (based on forward derivative and delta coefficients), which are then mapped to CFG terminal symbols. The CFG then allows estimation of the most likely interpretation of the meal assuming independence for each event.
The device is used in research as well as in clinical practice. It was first used to treat patients with anorexia nervosa and other eating disorders and subsequently to treat severely overweight patients.
Eating assisted by visual feedback has the following scientific basis. Animals, including humans, have evolved to eat many different foods, but they select what to eat under &#34;buffet&#34; conditions3,4. However, they are equipped, anatomically and behaviorally, to eat whatever foods are available if conditions get compromised3,4 and eating behavior, chewing in particular, has therefore been a main driver of the evolution of the human head, including the brain and the masticatory apparatus3. The pattern of eating may therefore be more important for the control of body weight than the kind of food eaten. In support, diet intervention has minor, if any, effect on normalizing body weight5 and the device described here can e.g., assist school children in eating a normal amount of food when challenged to eat quickly during the school lunch6 and reverse the effect of a brief period of fasting on food intake in young women and men7.
Neuroscience hypothesizes that the cause of weight problems is lodged in the brain8. However, it is unlikely that the hundreds of millions of people in the world, who now weigh too much9, developed the problem because of a neural abnormality before the weight gain. It is more likely that neural abnormalities10, as well as medical abnormalities11, develop as an effect of eating too much12, save, perhaps in some rare genotypes13.
A possible reason why neuroscience fails to explain the problems of body weight is because its basic assumption is incorrect, i.e., that body weight is kept nearly constant via excitatory/inhibitory neural controls exerted over eating behavior8. Whatever inhibition the brain may exert has obviously not prevented hundreds of millions of people to become seriously overweight recently9. A better understanding of the role of brain in eating emerged from the discovery that hypothalamic peptides once thought to stimulate eating act instead to permit the search for food, even at the expense of food intake14,15. These results, which were confirmed recently16,17, support the view that body weight is kept at a healthy level only when the physical price of food is high, a condition referred to as &#34;the human homeostatic phenoptype&#34;18. Considering the multiplicity of brain and genetic networks engaged in eating behavior and other behaviors also19, it would be difficult, if at all possible, to decrease or increase body weight by manipulating a neurotransmitter system or two. Given these consideration, it comes as no surprise that pharmacological intervention has minimal, or no effects on body weight in the seriously overweight20, as well as in the underweight21.
It is ironic that some of these recent findings merely confirm the predictions concerning the role of diets, genes, brain, and physical activity in body weight regulation made by Mayer in 1953 already22. As an alternative, eating behavior may have a causal role in the control of body weight and neuroscience and genetics may have mistaken mechanism for cause. In support, daily eating over the year strives to maximize food intake in humans, pushing body weight upwards to counteract any influence of food shortage23. In the human homeostatic phenotype, the influence of this kind of physiological overeating is counterbalanced by the physical effort needed to obtain food18. Because that effort is close to zero today humans need external support to maintain a healthy low body weight. That support is provided by the present device.
Rather than targeting eating behavior, standard treatments for eating disorders target the patients&#180; psychological symptoms. On average 30% of the patients drop out of these treatments, fewer than 50% go into remission, although they remain symptomatic, and at least 30% relapse within one year of discharge24. However, it was found long ago that treating eating behavior has a better effect than treating the psychological symptoms25. This finding was replicated more recently by using the device described in this report. By this method, an estimated 75% of patients with eating disorders go into remission and 10% relapse over five years of follow-up26, an improvement over standards of care24.
Although the rate of eating has increased in seriously overweight patients, the cause-effect relationship among rate of eating and body weight has not been clarified and the rate of eating has been determined by questionnaires27. The device described here makes objective measurement of eating rate and food intake possible and when used to reduce these two measures, it has been demonstrated to be more effective in decreasing body weight and improving health than standard diet and exercise intervention in severely overweight adolescents28.
The principle of recording eating behavior utilized in the present device was described long ago29,30,31, and it has since then been used in experiments to record and change the rate of eating1,6,7,32,33. However, it has not been used to treat under- and overweight patients outside of clinical trials and in clinical practice. Part of the clinical program involves using the device at home and in everyday life. It has proven to be user friendly in both laboratory research and in clinical practice.

<table border="0" cellpadding="0" cellspacing="0" width="849">
	<tbody>
		<tr height="40">
			<td height="40" style="height:30.0pt;width:162pt" width="216">Scale</td>
			<td style="width:92pt" width="122">T&#220;M ELEKTRONIK</td>
			<td style="width:258pt" width="344">no catalogue number</td>
			<td style="width:125pt" width="167">csutm made not comercially available</td>
		</tr>
	</tbody>
</table>

control of eating behavior using a novel feedback system

Subjects eat food from a plate that sits on a scale connected to a computer that records the weight loss of the plate during the meal and makes up a curve of food intake, meal duration and rate of eating modeled by a quadratic equation. The purpose of the method is to change eating behavior by providing visual feedback on the computer screen that the subject can adapt to because her/his own rate of eating appears on the screen during the meal. The data generated by the method is automatically analyzed and fitted to the quadratic equation using a custom made algorithm. The method has the advantage of recording eating behavior objectively and offers the possibility of changing eating behavior both in experiments and in clinical practice. A limitation may be that experimental subjects are affected by the method. The same limitation may be an advantage in clinical practice, as eating behavior is more easily stabilized by the method. A treatment that uses this method has normalized body weight and restored the health of several hundred patients with anorexia nervosa and other eating disorders and has reduced the weight and improved the health of severely overweight patients.

Five women, who were 17.5 (15-24) (median, min-max) years old, were treated to remission from anorexia nervosa. Figure 11, Figure 12, Figure 13 show the data generated by the device, the appearance of the CFI curve and the quadratic model in two recordings in the early part of treatment and a recording at the time of remission. Note the accelerating rate of eating in the first test without visual feedback, intake of a large meal already three days later with reference curve providing visual feedback and doubling of the rate of eating at the time of remission in comparison with the two recordings in the early part of treatment in one of the patients.
Figure 14A shows that the time to remission was very variable in the five patients. The figure also shows that with a normal Body Mass Index (BMI) at the time of remission (Figure 14B), the patients consumed more food than they did at admission (Figure 14C), and that the duration of the meal, although not reduced, was less variable (Figure 14D). Note that anorexics can consume a relatively large meal at admission with a low BMI (Figure 14C). It is also noteworthy that while three patients ate at an accelerating rate at admission, all but one ate at a decelerated rate when in remission (Figure 14E). Correlatively, the intitial rate of eating had increased at the time of remission (Figure 14F).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/57432/57432fig1.jpg" /> 
Figure 1: The scale. Press button to turn on the scale. <a href="/files/ftp_upload/57432/57432fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/57432/57432fig2.jpg" /> 
Figure 2: Start meal. Open app to start meal. Press Control to eat without visual feedback. Press Training to eat with visual feedback. <a href="/files/ftp_upload/57432/57432fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/57432/57432fig3.jpg" /> 
Figure 3: Connect scale and smartphone. Select scale using app. Press Connect to proceed. <a href="/files/ftp_upload/57432/57432fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/57432/57432fig4.jpg" /> 
Figure 4: Put plate on scale. Put plate on the scale and press Done to proceed. <a href="/files/ftp_upload/57432/57432fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/57432/57432fig5.jpg" /> 
Figure 5: Put food on plate. Put food on the plate until 100% is indicated and press Start when ready to eat. <a href="/files/ftp_upload/57432/57432fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/57432/57432fig6.jpg" /> 
Figure 6: Eating with visual feedback. Adapt rate of eating to dashed blue reference curve. <a href="/files/ftp_upload/57432/57432fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/57432/57432fig7.jpg" /> 
Figure 7: Rating of fullness. Indicate feeling of fullness when rating scale appears. Adapt rating to dashed purple reference curve and press Done to continue eating. <a href="/files/ftp_upload/57432/57432fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/57432/57432fig8.jpg" /> 
Figure 8: Adapting rate of eating. Modify rate of eating if deviating from dashed blue reference curve. <a href="/files/ftp_upload/57432/57432fig8large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 9" class="xfigimg" src="/files/ftp_upload/57432/57432fig9.jpg" /> 
Figure 9: Meal completed. Press No if there is no food on the plate. <a href="/files/ftp_upload/57432/57432fig9large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 10" class="xfigimg" src="/files/ftp_upload/57432/57432fig10.jpg" /> 
Figure 10: Meal finished. Compliance to references curves and duration of meal displayed. Press Done to exit. <a href="/files/ftp_upload/57432/57432fig10large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 11" class="xfigimg" src="/files/ftp_upload/57432/57432fig11.jpg" /> 
Figure 11: Early cumulative food intake (CFI) curve in anorexia nervosa. Recording (blue line), artifacts removed (red line) and CFI curve modeled by quadratic equation. Data from an anorexic patient on the second day of treatment eating without visual feedback. <a href="/files/ftp_upload/57432/57432fig11large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 12" class="xfigimg" src="/files/ftp_upload/57432/57432fig12.jpg" /> 
Figure 12: Early response to treatment in anorexia nervosa. Patient adapts to reference curve on the fifth day of treatment. Data from the same patient. <a href="/files/ftp_upload/57432/57432fig12large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 13" class="xfigimg" src="/files/ftp_upload/57432/57432fig13.jpg" /> 
Figure 13: Remission from anorexia nervosa. Increase in the rate of eating at time of remission after 175 days of treatment. Data from the same patient eating without visual feedback. <a href="/files/ftp_upload/57432/57432fig13large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 14" class="xfigimg" src="/files/ftp_upload/57432/57432fig14.jpg" /> 
Figure 14: Effect of treating eating behavior in anorexia nervosa. Time to remission highly variable (A) as Body Mass Index (BMI) normalizes (B) in five patients treated to remission from anorexia nervosa. Note variability in food intake (C), meal duration (D), deceleration of the rate of eating (E) and the initial rate of eating (F) at admission (Adm) and normalization of these measures at remission (Rem). Patients eating without reference curve. Data are medians (min-max). <a href="/files/ftp_upload/57432/57432fig14large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Control of Eating Behavior Using a Novel Feedback System at JoVE.com

Control of Eating Behavior Using a Novel Feedback System

Subjects eat food from a plate placed on a scale connected to a computer that records the weight loss of the plate during the meal. Feedback on the computer screen allows the subject to adapt her/his eating behavior to reference curves thus normalizing body weight.

Subjects eat food from a plate that sits on a scale connected to a computer that records the weight loss of the plate during the meal and makes up a curve ...

control-of-eating-behavior-using-a-novel-feedback-system

Nanyang Technological University

Research

JoVE Journal

Behavior

10.8K Views.  Karolinska Institutet. Subjects eat food from a plate placed on a scale connected to a computer that records the weight loss of the plate during the meal. Feedback on the computer screen allows the subject to adapt her/his eating behavior to reference curves thus normalizing body weight.

Video: Control of Eating Behavior Using a Novel Feedback System

Contextual and Cued Fear Conditioning Test Using a Video Analyzing System in Mice

The contextual and cued fear conditioning test is one of the behavioral tests that assesses the ability of mice to learn and remember an association between environmental cues and aversive experiences. In this test, mice are placed into a conditioning chamber and are given parings of a conditioned stimulus (an auditory cue) and an aversive unconditioned stimulus (an electric footshock). After a delay time, the mice are exposed to the same conditioning chamber and a differently shaped chamber with presentation of the auditory cue. Freezing behavior during the test is measured as an index of fear memory. To analyze the behavior automatically, we have developed a video analyzing system using the ImageFZ application software program, which is available as a free download at http://www.mouse-phenotype.org/. Here, to show the details of our protocol, we demonstrate our procedure for the contextual and cued fear conditioning test in C57BL/6J mice using the ImageFZ system. In addition, we validated our protocol and the video analyzing system performance by comparing freezing time measured by the ImageFZ system or a photobeam-based computer measurement system with that scored by a human observer. As shown in our representative results, the data obtained by ImageFZ were similar to those analyzed by a human observer, indicating that the behavioral analysis using the ImageFZ system is highly reliable. The present movie article provides detailed information regarding the test procedures and will promote understanding of the experimental situation.

This article presents a protocol for a contextual and cued fear conditioning test using a video analyzing system to assess fear learning and memory in mice.

The contextual and cued fear conditioning test is one of the behavioral tests that assesses the ability of mice to learn and remember an association ...

Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach

The main goal of this study was to assess the usability of a tablet-computer-based application (EmoCogMeter) in investigating the effects of age on cognitive functions across the lifespan in a sample of 378 healthy subjects (age range 18-89 years). Consistent with previous findings we found an age-related cognitive decline across a wide range of neuropsychological domains (memory, attention, executive functions), thereby proving the usability of our tablet-based application. Regardless of prior computer experience, subjects of all age groups were able to perform the tasks without instruction or feedback from an experimenter. Increased motivation and compliance proved to be beneficial for task performance, thereby potentially increasing the validity of the results. Our promising findings underline the great clinical and practical potential of a tablet-based application for detection and monitoring of cognitive dysfunction.

We tested the usability of a tablet-computer-based application (EmoCogMeter) in investigating the effects of age on cognition. Results show an age-related cognitive decline, thereby proving the usability of our application. Findings underline the great clinical and practical potential of a tablet-based application for detection and monitoring of cognitive dysfunction.

The main goal of this study was to assess the usability of a tablet-computer-based application (EmoCogMeter) in investigating the effects of age on ...

Assessing Forelimb Function after Unilateral Cervical SCI using Novel Tasks: Limb Step-alternation, Postural Instability and Pasta Handling

Cervical spinal cord injury (cSCI) can cause devastating neurological deficits, including impairment or loss of upper limb and hand function. A majority of the spinal cord injuries in humans occur at the cervical levels. Therefore, developing cervical injury models and developing relevant and sensitive behavioral tests is of great importance. Here we describe the use of a newly developed forelimb step-alternation test after cervical spinal cord injury in rats. In addition, we describe two behavioral tests that have not been used after spinal cord injury: a postural instability test (PIT), and a pasta-handling test. All three behavioral tests are highly sensitive to injury and are easy to use. Therefore, we feel that these behavioral tests can be instrumental in investigating therapeutic strategies after cSCI.

Three new behavioral tests (forelimb step-alternation, postural instability test, pasta handling test) for evaluating forelimb function after cervical spinal cord injury in rodents are described.

Cervical spinal cord injury (cSCI) can cause devastating neurological deficits, including impairment or loss of upper limb and hand function. A majority ...

The 5-Choice Serial Reaction Time Task: A Task of Attention and Impulse Control for Rodents

This protocol describes the 5-choice serial reaction time task, which is an operant based task used to study attention and impulse control in rodents. Test day challenges, modifications to the standard task, can be used to systematically tax the neural systems controlling either attention or impulse control. Importantly, these challenges have consistent effects on behavior across laboratories in intact animals and can reveal either enhancements or deficits in cognitive function that are not apparent when rats are only tested on the standard task. The variety of behavioral measures that are collected can be used to determine if other factors (i.e., sedation, motivation deficits, locomotor impairments) are contributing to changes in performance. The versatility of the 5CSRTT is further enhanced because it is amenable to combination with pharmacological, molecular, and genetic techniques.

This protocol describes the 5-choice serial reaction time task, which is an operant based task used to study attention and impulse control in rodents. Test day challenges, which are modifications of the standard task, increase flexibility of the task and can be combined with other manipulations to more fully characterize behavior.

This protocol describes the 5-choice serial reaction time task, which is an operant based task used to study attention and impulse control in rodents. ...

Fat Preference: A Novel Model of Eating Behavior in Rats

Obesity is a growing problem in the United States of America, with more than a third of the population classified as obese. One factor contributing to this multifactorial disorder is the consumption of a high fat diet, a behavior that has been shown to increase both caloric intake and body fat content. However, the elements regulating preference for high fat food over other foods remain understudied.
To overcome this deficit, a model to quickly and easily test changes in the preference for dietary fat was developed. The Fat Preference model presents rats with a series of choices between foods with differing fat content. Like humans, rats have a natural bias toward consuming high fat food, making the rat model ideal for translational studies. Changes in preference can be ascribed to the effect of either genetic differences or pharmacological interventions. This model allows for the exploration of determinates of fat preference and screening pharmacotherapeutic agents that influence acquisition of obesity.

Dietary fat content influences both energy intake and body fat composition in mammals. By examining rats&#8217; preference for high fat food in a series of choice experiments, it is possible to test genetic differences and pharmacological interventions on their preference for high fat food.

Obesity is a growing problem in the United States of America, with more than a third of the population classified as obese. One factor contributing to ...

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Advances in robotic systems have resulted in prostheses for the upper limb that can produce multifunctional movements. However, these sophisticated systems require upper limb amputees to learn complex control schemes. Humans have the ability to learn new movements through imitation and other learning strategies. This protocol describes a structured rehabilitation method, which includes imitation, repetition, and reinforcement learning, and aims to assess if this method can improve multifunctional prosthetic control. A left below elbow amputee, with 4 years of experience in prosthetic use, took part in this case study. The prosthesis used was a Michelangelo hand with wrist rotation, and the added features of wrist flexion and extension, which allowed more combinations of hand movements. The participant&#8217;s Southampton Hand Assessment Procedure score improved from 58 to 71 following structured training. This suggests that a structured training protocol of imitation, repetition and reinforcement may have a role in learning to control a new prosthetic hand. A larger clinical study is however required to support these findings.

As prosthetic development moves towards the goal of natural control, harnessing amputees&#8217; inherent ability to learn new motor skills may enable proficiency. This manuscript describes a structured rehabilitation protocol, which includes imitation, repetition, and reinforcement learning strategies, for improved multifunctional prosthetic control.

Advances in robotic systems have resulted in prostheses for the upper limb that can produce multifunctional movements. However, these sophisticated ...

Force and Position Control in Humans - The Role of Augmented Feedback

During motor behaviour, humans interact with the environment by for example manipulating objects and this is only possible because sensory feedback is constantly integrated into the central nervous system and these sensory inputs need to be weighted in order meet the task specific goals. Additional feedback presented as augmented feedback was shown to have an impact on motor control and motor learning. A number of studies investigated whether force or position feedback has an influence on motor control and neural activation. However, as in the previous studies the presentation of the force and position feedback was always identical, a recent study assessed whether not only the content but also the interpretation of the feedback has an influence on the time to fatigue of a sustained submaximal contraction and the (inhibitory) activity of the primary motor cortex using subthreshold transcranial magnetic stimulation. This paper describes one possible way to investigate the influence of the interpretation of feedback on motor behaviour by investigating the time to fatigue of submaximal sustained contractions together with the neuromuscular adaptations that can be investigated using surface EMG. Furthermore, the current protocol also describes how motor cortical (inhibitory) activity can be investigated using subthreshold TMS, a method known to act solely on the cortical level. The results show that when participants interpret the feedback as position feedback, they display a significantly shorter time to fatigue of a submaximal sustained contraction. Furthermore, subjects also displayed an increased inhibitory activity of the primary cortex when they believed to receive position feedback compared when they believed to receive force feedback. Accordingly, the results show that interpretation of feedback results in differences on a behavioural level (time to fatigue) that is also reflected in interpretation-specific differences in the amount of inhibitory M1 activity.

Controlling an identical movement with position or force feedback results in different neural activation and motor behavior. This protocol describes how to investigate behavioral changes by looking at neuromuscular fatigue and how to evaluate motor cortical (inhibitory) activity using subthreshold TMS with respect to the interpretation of augmented feedback.

During motor behaviour, humans interact with the environment by for example manipulating objects and this is only possible because sensory feedback is ...

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb

Individuals with sensorimotor pathology e.g., stroke have difficulty executing the common task of rising from sitting and initiating gait (sit-to-walk: STW). Thus, in clinical rehabilitation separation of sit-to-stand and gait initiation - termed sit-to-stand-and-walk (STSW) - is usual. However, a standardized STSW protocol with a clearly defined analytical approach suitable for pathological assessment has yet to be defined.
Hence, a goal-orientated protocol is defined that is suitable for healthy and compromised individuals by requiring the rising phase to be initiated from 120% knee height with a wide base of support independent of lead limb. Optical capture of three-dimensional (3D) segmental movement trajectories, and force platforms to yield two-dimensional (2D) center-of-pressure (COP) trajectories permit tracking of the horizontal distance between COP and whole-body-center-of-mass (BCOM), the decrease of which increases positional stability but is proposed to represent poor dynamic postural control.
BCOM-COP distance is expressed with and without normalization to subjects&#39; leg length. Whilst COP-BCOM distances vary through STSW, normalized data at the key movement events of seat-off and initial toe-off (TO1) during steps 1 and 2 have low intra and inter subject variability in 5 repeated trials performed by 10 young healthy individuals. Thus, comparing COP-BCOM distance at key events during performance of an STSW paradigm between patients with upper motor neuron injury, or other compromised patient groups, and normative data in young healthy individuals is a novel methodology for evaluation of dynamic postural stability.

Here, we present a novel protocol to measure positional stability at key events during the sit-to-stand-to-walk using the center-of-pressure to the whole-body-center-of-mass distance. This was derived from the force platform and three-dimensional motion-capture technology. The paradigm is reliable and can be utilized for the assessment of neurologically compromised individuals.

Individuals with sensorimotor pathology e.g., stroke have difficulty executing the common task of rising from sitting and initiating gait (sit-to-walk: ...

A Novel Single Animal Motor Function Tracking System Using Simple, Readily Available Software

We have recently demonstrated that implanting intracortical microelectrodes in the motor corteces of rats&#160;results in immediate and lasting motor deficits. Motor impairments were manually quantified through an open field grid test to measure the gross motor function and through a ladder test to measure the fine motor function. Here, we discuss a technique for the automated quantification of the video-recorded tests using our custom Capadona Behavioral Video Analysis System: Grid and Ladder Test, or BVAS. Leveraging simple and readily available coding software (see the Table of Materials), this program allows for the tracking of a single animal on both the open field grid and the ladder tests. In open field grid tracking, the code thresholds the video for intensity, tracks the position of the rat over the 3 min duration of the grid test, and analyzes the path. It then computes and returns measurements for the total distance traveled, the maximum velocity achieved, the number of left- and right-handed turns, and the total number of grid lines crossed by the rat. In ladder tracking, the code again thresholds the video for intensity, tracks the movement of the rat across the ladder, and returns calculated measurements including the time it took the rat to cross the ladder, the number of paw slips occurring below the plane of the ladder rungs, and the incidence of failures due to stagnation or reversals. We envision that the BVAS developed here can be employed for the analysis of motor function in a variety of applications, including many injury or disease models.

The current study aimed to automate the quantification of motor deficits in rats. The initial evaluation model assesses motor loss resulting from an intracortical microelectrode implantation in the motor cortex. We report on the development and use of a tracking algorithm using easily adaptable, simple, and readily available coding software.

We have recently demonstrated that implanting intracortical microelectrodes in the motor corteces of rats&#160;results in immediate and lasting motor ...

A Vibrotactile Feedback Device for Seated Balance Assessment and Training

Postural perturbations, motion tracking, and sensory feedback are modern techniques used to challenge, assess, and train upright sitting, respectively. The goal of the developed protocol is to construct and operate a sitting platform that can be passively destabilized while an inertial measurement unit quantifies its motion and vibrating elements deliver tactile feedback to the user. Interchangeable seat attachments alter the stability level of the device to safely challenge sitting balance. A built-in microcontroller allows fine-tuning of the feedback parameters to augment sensory function. Posturographic measures, typical of balance assessment protocols, summarize the motion signals acquired during timed balance trials. No dynamic sitting protocol to date provides variable challenge, quantification, and sensory feedback free of laboratory constraints. Our results demonstrate that non-disabled users of the device exhibit significant changes in posturographic measures when balance difficulty is altered or vibrational feedback provided. The portable, versatile device has potential applications in rehabilitation (following skeletal, muscular, or neurological injury), training (for sports or spatial awareness), entertainment (via virtual or augmented reality), and research (of sitting-related disorders).

A sitting platform has been developed and assembled that passively destabilizes sitting posture in humans. During the user&#39;s stabilizing task, an inertial measurement unit records the device&#39;s motion, and vibrating elements deliver performance-based feedback to the seat. The portable, versatile device may be used in rehabilitation, assessment, and training paradigms.

Postural perturbations, motion tracking, and sensory feedback are modern techniques used to challenge, assess, and train upright sitting, respectively. ...