Positive Technology Journal

Moodscope is "an online personal mood management tool that helps people grappling with depression or mood disorders to effectively measure and track their moods". It allows tracking your "ups and downs" and displaying them on a graph to better understand how your mood fluctuates over time. And yes, of course it allows sharing your scores with trusted friends so they can support you if you are down..

Positive Technology: Using Interactive Technologies to Promote Positive Functioning

G. Riva, R.M. Baños, C. Botella, B.K. Wiederhold, A. Gaggioli

Cyberpsychology, Behavior, and Social Networking (Online Ahead of Print: December 9, 2011) DOI

A team of three designers, Oleg Imanilov, Zvika Markfield, and Tomer Daniel, have recently developed a novel sign language interpreter glove. Basically, the glove works as an input device from which the user is able to use sign language to create a text message. The hw system consists of AD board, gyroscope, finger sensor, Lilypad Adriano and an accelerometer. The prototype was demonstrated at a recent Google developers event in Tel Aviv, and can be seen in the video below.

MIT's Technology Review reports that Samsung researchers have released a smart-phone designed to "read" people's emotions. Rather than relying on specialized sensors or cameras, the phone infers a user's emotional state based on how he's using the phone.

"For example, it monitors certain inputs, such as the speed at which a user types, how often the “backspace” or “special symbol” buttons are pressed, and how much the device shakes. These measures let the phone postulate whether the user is happy, sad, surprised, fearful, angry, or disgusted, says Hosub Lee, a researcher with Samsung Electronics and the Samsung Advanced Institute of Technology’s Intelligence Group, in South Korea. Lee led the work on the new system. He says that such inputs may seem to have little to do with emotions, but there are subtle correlations between these behaviors and one’s mental state, which the software’s machine-learning algorithms can detect with an accuracy of 67.5 percent."

Once a phone infers an emotional state, it can then change how it interacts with the user: "The system could trigger different ringtones on a phone to convey the caller’s emotional state or cheer up someone who’s feeling low. “The smart phone might show a funny cartoon to make the user feel better,” he says.

Cued motor imagery in patients with multiple sclerosis.

Neuroscience. 2012 Jan 8

Authors: Heremans E, Nieuwboer A, Spildooren J, Bondt SD, D'hooge AM, Helsen W, Feys P

Abstract. Motor imagery (MI) is a promising practice tool in neurorehabilitation. However, in patients with multiple sclerosis (MS), impairments in MI accuracy and temporal organization were found during clinical assessment, which may limit the benefits of MI practice. Therefore, we investigated whether the MI quality of MS patients could be optimized by means of external cueing. Fourteen patients with MS and 14 healthy control patients physically executed and visually imagined a goal-directed upper limb task in the presence and absence of added visual and auditory cues. MI quality was assessed by means of eye-movement registration. As main results, it was found that MS patients had significant higher eye-movement times than controls during both execution and imagery, and overestimated the to-be-imagined movement amplitude when no external information was provided during imagery. External cues, however, decreased patients' MI duration and increased the spatial accuracy of their imagined movements. In sum, our results indicate that MS patients imagine movements in a better way when they are provided with external cues during MI. These findings are important for developing rehabilitation strategies based on MI in patients with MS.

A combined robotic and cognitive training for locomotor rehabilitation: evidences of cerebral functional reorganization in two chronic traumatic brain injured patients.

Front Hum Neurosci. 2011;5:146

Authors: Sacco K, Cauda F, D'Agata F, Duca S, Zettin M, Virgilio R, Nascimbeni A, Belforte G, Eula G, Gastaldi L, Appendino S, Geminiani G

Abstract. It has been demonstrated that automated locomotor training can improve walking capabilities in spinal cord-injured subjects but its effectiveness on brain damaged patients has not been well established. A possible explanation of the discordant results on the efficacy of robotic training in patients with cerebral lesions could be that these patients, besides stimulation of physiological motor patterns through passive leg movements, also need to train the cognitive aspects of motor control. Indeed, another way to stimulate cerebral motor areas in paretic patients is to use the cognitive function of motor imagery. A promising possibility is thus to combine sensorimotor training with the use of motor imagery. The aim of this paper is to assess changes in brain activations after a combined sensorimotor and cognitive training for gait rehabilitation. The protocol consisted of the integrated use of a robotic gait orthosis prototype with locomotor imagery tasks. Assessment was conducted on two patients with chronic traumatic brain injury and major gait impairments, using functional magnetic resonance imaging. Physiatric functional scales were used to assess clinical outcomes. Results showed greater activation post-training in the sensorimotor and supplementary motor cortices, as well as enhanced functional connectivity within the motor network. Improvements in balance and, to a lesser extent, in gait outcomes were also found.