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PulseRide: A Robotic Wheelchair for Personalized Exertion Control with Human-in-the-Loop Reinforcement Learning

Zahid, Azizul, Poudel, Bibek, Scott, Danny, Scott, Jason, Crouter, Scott, Li, Weizi, Swaminathan, Sai

arXiv.org Artificial Intelligence

Maintaining an active lifestyle is vital for quality of life, yet challenging for wheelchair users. For instance, powered wheelchairs face increasing risks of obesity and deconditioning due to inactivity. Conversely, manual wheelchair users, who propel the wheelchair by pushing the wheelchair's handrims, often face upper extremity injuries from repetitive motions. These challenges underscore the need for a mobility system that promotes activity while minimizing injury risk. Maintaining optimal exertion during wheelchair use enhances health benefits and engagement, yet the variations in individual physiological responses complicate exertion optimization. To address this, we introduce PulseRide, a novel wheelchair system that provides personalized assistance based on each user's physiological responses, helping them maintain their physical exertion goals. Unlike conventional assistive systems focused on obstacle avoidance and navigation, PulseRide integrates real-time physiological data-such as heart rate and ECG-with wheelchair speed to deliver adaptive assistance. Using a human-in-the-loop reinforcement learning approach with Deep Q-Network algorithm (DQN), the system adjusts push assistance to keep users within a moderate activity range without under- or over-exertion. We conducted preliminary tests with 10 users on various terrains, including carpet and slate, to assess PulseRide's effectiveness. Our findings show that, for individual users, PulseRide maintains heart rates within the moderate activity zone as much as 71.7 percent longer than manual wheelchairs. Among all users, we observed an average reduction in muscle contractions of 41.86 percent, delaying fatigue onset and enhancing overall comfort and engagement. These results indicate that PulseRide offers a healthier, adaptive mobility solution, bridging the gap between passive and physically taxing mobility options.


Autonomation • TechCrunch

#artificialintelligence

"Jidoka" is a new one to me. TRI (Toyota Research Institute) CEO Gill Pratt described the concept as "Automation with a Human Touch." The anglicized version of the notion is "Autonomation" -- both are modified forms of " automation," in their respective languages. The word was originally applied to Toyota's Production System, highlighting the need for human participation in the process. Employing Jidoka principles throughout the production process is a vital element of the Toyota Production System, forcing imperfections to be immediately addressed by self-inspecting workers and thereby reducing the amount of work added to a defective product.


Hidden Pentagon records reveal patterns of failure in deadly U.S. airstrikes

The Japan Times

Shortly before 3 a.m. on July 19, 2016, U.S. Special Operations forces bombed what they believed were three Islamic State (IS) group "staging areas" on the outskirts of Tokhar, a riverside hamlet in northern Syria. They reported 85 fighters killed. In fact, they hit houses far from the front line, where farmers, their families and other local people sought nighttime sanctuary from bombing and gunfire. More than 120 villagers were killed. In early 2017 in Iraq, an American war plane struck a dark-colored vehicle, believed to be a car bomb, stopped at an intersection in the Wadi Hajar neighborhood of West Mosul. Actually, the car had been bearing not a bomb but a man named Majid Mahmoud Ahmed, his wife and their two children, who were fleeing the fighting nearby. They and three other civilians were killed. In November 2015, after observing a man dragging an "unknown heavy object" into an IS "defensive fighting position," U.S. forces struck a building in Ramadi, Iraq. A military review found that the object was actually "a person of small stature" -- a child -- who died in the strike. None of these deadly failures resulted in a finding of wrongdoing. These cases are drawn from a hidden Pentagon archive of the American air war in the Middle East since 2014. The trove of documents -- the military's own confidential assessments of more than 1,300 reports of civilian casualties, obtained by The New York Times -- lays bare how the air war has been marked by deeply flawed intelligence, rushed and often imprecise targeting and the deaths of thousands of civilians, many of them children, a sharp contrast to the U.S. government's image of war waged by all-seeing drones and precision bombs. The documents show, too, that despite the Pentagon's highly codified system for examining civilian casualties, pledges of transparency and accountability have given way to opacity and impunity. In only a handful of cases were the assessments made public. Not a single record provided includes a finding of wrongdoing or disciplinary action. Fewer than a dozen condolence payments were made, even though many survivors were left with disabilities requiring expensive medical care. Documented efforts to identify root causes or lessons learned are rare. The air campaign represents a fundamental transformation of warfare that took shape in the final years of the Obama administration, amid the deepening unpopularity of the forever wars that had claimed more than 6,000 American service members. The United States traded many of its boots on the ground for an arsenal of aircraft directed by controllers sitting at computers, often thousands of kilometers away. President Barack Obama called it "the most precise air campaign in history." This was the promise: America's "extraordinary technology" would allow the military to kill the right people while taking the greatest possible care not to harm the wrong ones. The IS caliphate ultimately crumbled under the weight of American bombing.


For Iraqi soldiers coordinating coalition strikes on Islamic State, it's a different kind of war

Los Angeles Times

The two Islamic State jihadis scrambled up to the roof of the building, breaking cover for a moment before quickly hiding from sight. But it was too late. They had been spotted by the camera drone hovering above Mosul's Old City, their images beamed to black-clad special forces operatives huddled around a tablet roughly 300 yards away. Lt. Col. Muhannad Tamimi, a battalion commander, turned to his walkie-talkie. "Staff Col. Arkan," he said.


ISIL ramps up fight with weaponised drones

Al Jazeera

Mosul, Iraq - As fighting raged in eastern Mosul on a recent afternoon, a black Humvee arrived at an Iraqi army command post with a collection of plastics, electronics and rotor blades lashed to its back. Soldiers leaped to unload the cargo, which comprised the remnants of the latest tool in ISIL's armoury: drones. The haul included a number of small devices of the kind favoured by filmmakers and hobbyists, costing a few hundred dollars apiece. But there were also larger, fixed-wing craft fashioned out of corrugated plastic and duct tape, apparently made by the fighters themselves. Since mid-2014, the Islamic State of Iraq and the Levant (ISIL, also known as ISIS) group has held Mosul, after sweeping through northern Iraq in a shock offensive.


Influential Node Detection in Implicit Social Networks using Multi-task Gaussian Copula Models

Li, Qunwei, Kailkhura, Bhavya, Thiagarajan, Jayaraman J., Zhang, Zhenliang, Varshney, Pramod K.

arXiv.org Machine Learning

Influential node detection is a central research topic in social network analysis. Many existing methods rely on the assumption that the network structure is completely known \textit{a priori}. However, in many applications, network structure is unavailable to explain the underlying information diffusion phenomenon. To address the challenge of information diffusion analysis with incomplete knowledge of network structure, we develop a multi-task low rank linear influence model. By exploiting the relationships between contagions, our approach can simultaneously predict the volume (i.e. time series prediction) for each contagion (or topic) and automatically identify the most influential nodes for each contagion. The proposed model is validated using synthetic data and an ISIS twitter dataset. In addition to improving the volume prediction performance significantly, we show that the proposed approach can reliably infer the most influential users for specific contagions.


What We Know About ISIS's Scratch-built Drones

Popular Science

To better understand ISIS drones, I spoke with an investigator at Conflict Armament research, who requested anonymity given the sensitive nature of the work. When the investigator entered the workshop, there were no completed drones inside. Instead, they saw plywood fuselages and styrofoam wings, as well as a missile from a man-portable anti-air defense system, or MANPADS. "For us it implied that they were trying to arm it, arm their drones with something that would be light enough to be carried by a drone, but also that would have the right kind of explosives for potency," they said. Many of their finding were published in a report on the Islamic State's Weaponized Drones.


Captured battlefield cellphones, computers help U.S. target and kill Islamic State's leaders

Los Angeles Times

U .S. military officers watched grainy video feeds at a small operations center in Baghdad on Tuesday as Predator drones tracked and killed three reputed Islamic State leaders -- one after another -- in the offensive on Mosul. The targeted air strikes were due in large part to intelligence extracted from cellphones, computer hard drives, memory cards and hand-written ledgers recovered from battlefields and towns taken from Islamic State fighters. Recently captured intelligence also has proved useful in providing clues to detecting potential terrorist plots, tracking foreign fighters and identifying Islamic State supporters around the globe, U.S. officials said. The largest data trove was recovered when U.S.-backed Syrian rebel forces recaptured Manbij, an Islamic State stronghold in northern Syria, in mid-August. Intelligence agencies recovered more than 120,000 documents, nearly 1,200 devices and more than 20 terabytes of digital information, officials said. Islamic State militants came early in the morning, riding atop trucks that lumbered into this northern Iraqi oil town.


Iraq: ICRC camera drone captures damage in Ramadi

Al Jazeera

Chilling aerial footage of Ramadi, a once bustling city in central Iraq, has captured the extent of destruction caused by war. In late December, Iraqi forces, backed by US air strikes, announced the recapturing of Ramadi, which had been lost to the Islamic State of Iraq and the Levant (ISIL, also known as ISIS) group in May 2015. The US-led coalition carried out more than 600 air strikes in the area from July to December last year. A new six-minute clip, released by the International Red Committee of The Red Cross (ICRC) shows homes in Ramadi turned to rubble, along with flattened school, destroyed hospitals and damaged ambulances. READ MORE: Dramatic video'shows destruction of huge ISIL convoy' "Rare aerial footage gathered by ICRC shows the once prosperous Ramadi in central Iraq now in tatters - a ghost town," the ICRC said on Monday.