Browse content similar to 02/09/2017. Check below for episodes and series from the same categories and more!
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Newswatch will be here in 15 minutes' time. | :00:00. | :00:09. | |
Believe it or not, modern nursing as we know it only dates back | :00:10. | :00:32. | |
to the 1800s, to the time of Florence Nightingale | :00:33. | :00:34. | |
The Royal College of Nursing, here in London, | :00:35. | :00:40. | |
is now in its 101st year. | :00:41. | :00:43. | |
For all the life-saving technology that we've seen, | :00:44. | :00:48. | |
the actual act of nursing itself is one relationship that so far has | :00:49. | :00:52. | |
And in the UK, a quarter will be over 65 by 2045. | :00:53. | :01:05. | |
This all means that the pressures on nursing are increasing, | :01:06. | :01:10. | |
and looking after elderly people is becoming a pressing issue | :01:11. | :01:13. | |
Kat Hawkins travelled to Helsinki, in Finland, to discover whether one | :01:14. | :01:19. | |
of these could become the new one of these. | :01:20. | :01:29. | |
I'm here in Helsinki, visiting the home of Marja Roth | :01:30. | :01:32. | |
Hello! Hello, how are you? | :01:33. | :01:38. | |
Nice to meet you! Nice meeting you! | :01:39. | :01:47. | |
She is an ex-air hostess, who likes to keep active | :01:48. | :01:50. | |
Look at the hat as well. That was ages ago! | :01:51. | :01:55. | |
But, after a skiing accident a few years ago, she developed epilepsy. | :01:56. | :01:58. | |
I was unconscious for a little while, then got up and skied, | :01:59. | :02:03. | |
Her epilepsy means she needs daily medication and that her family, | :02:04. | :02:11. | |
who live in New York, want to make sure she's OK. | :02:12. | :02:15. | |
They get this reassurance from her daily nursing visit, | :02:16. | :02:17. | |
Do you think that this is as good as a nursing visit? | :02:18. | :02:24. | |
It's better because they see, actually physical, see me, | :02:25. | :02:27. | |
and then I don't have to wait for somebody to come. | :02:28. | :02:31. | |
They want to check basically that I - ask if I took | :02:32. | :02:34. | |
my pill, and... And just see how you are? | :02:35. | :02:36. | |
How I... Yeah. | :02:37. | :02:40. | |
Face, actually, to see the picture, to see that I'm OK. | :02:41. | :02:43. | |
At the other end of the line is Tuomo Kuivamaki. | :02:44. | :02:46. | |
He is one of the nurses here in Helsinki's first | :02:47. | :02:48. | |
Here, teams of trained nurses each make up to 50 video calls per day | :02:49. | :02:53. | |
to people around the city who need support. | :02:54. | :02:55. | |
So you've still got that kind of real human... | :02:56. | :02:58. | |
And especially some of the older customers, that's like a highlight | :02:59. | :03:01. | |
of the day for them, to have sort of a small chat | :03:02. | :03:05. | |
The hope is that this will cut down on the number of home visits that | :03:06. | :03:14. | |
nurses have to do to people who don't need physical support, | :03:15. | :03:17. | |
freeing up more time for those that do. | :03:18. | :03:20. | |
The software itself, called Video Visit, works much | :03:21. | :03:22. | |
So, while the tech isn't that new, Helsinki is unique in how wisely | :03:23. | :03:28. | |
the government is using it, and that can mean big | :03:29. | :03:31. | |
An in-person nursing visit can cost around 40 euros, | :03:32. | :03:34. | |
but this new type of checkup costs as little as five. | :03:35. | :03:41. | |
And what really comes across, watching this call, | :03:42. | :03:43. | |
And it just shows that that nursing element, | :03:44. | :03:50. | |
that real human connection, is still there, even though it's | :03:51. | :03:52. | |
People do hesitate at technology, and especially in nursing. | :03:53. | :03:56. | |
We are actually taking care of people. | :03:57. | :04:00. | |
It's scary that the robots are coming and taking our jobs. | :04:01. | :04:05. | |
Actually, the robots are in here already, | :04:06. | :04:07. | |
but they are easing our job, and actually giving us the freedom | :04:08. | :04:11. | |
to focus on people who actually need our physical help. | :04:12. | :04:21. | |
Now, medical technologies, of course, are improving | :04:22. | :04:25. | |
One example is the use of wearable technology | :04:26. | :04:27. | |
Now, this can be transformative for people with conditions | :04:28. | :04:31. | |
like facial palsy, Parkinson's and autism, | :04:32. | :04:33. | |
allowing them to control devices remotely, or even | :04:34. | :04:35. | |
My name is Bethan Robertson-Smith, and I'm doing my daily routine. | :04:36. | :04:45. | |
It's a series of exercises to flex the muscles in my face. | :04:46. | :04:48. | |
In 2008, when I was at university studying to be a veterinary nurse, | :04:49. | :04:52. | |
I had a fractured skull, an acquired brain injury, | :04:53. | :05:00. | |
and I was left with facial palsy, also known as facial paralysis. | :05:01. | :05:05. | |
It meant that every one of the 40 muscles that gave expression | :05:06. | :05:08. | |
Years later, I had an operation that allowed me to smile | :05:09. | :05:20. | |
like a Mona Lisa, using just two of the chewing muscles that | :05:21. | :05:23. | |
It's very hard to know exactly what muscles I need to move | :05:24. | :05:28. | |
I came down to Brighton today to try out a new piece of technology that's | :05:29. | :05:39. | |
going to help people like myself, who have got facial palsy. | :05:40. | :05:42. | |
One of the surgeons who operated on me is part of a team of experts | :05:43. | :05:46. | |
developing technologies with sensors to read the muscle activities | :05:47. | :05:49. | |
So, when you were first diagnosed, you had an examination called | :05:50. | :05:58. | |
the needle EMG, where the needle is put into the skin, | :05:59. | :06:01. | |
into the muscles, to read the tiny electrical signals | :06:02. | :06:04. | |
With this technology, what we're using is these sensors | :06:05. | :06:07. | |
So the same kind of reading, but without the pain, | :06:08. | :06:11. | |
You have some degree of crossover between the muscles, | :06:12. | :06:16. | |
and that's why you need the machine learning | :06:17. | :06:20. | |
to interpret which muscle is activating. | :06:21. | :06:24. | |
I'm Sarah Healey, and 30 years ago, I had a brain tumour. | :06:25. | :06:28. | |
Try to raise both eyebrows symmetrically. | :06:29. | :06:29. | |
The operation to take it out left me with paralysis on the right-hand | :06:30. | :06:35. | |
I am certainly not alone, as there are about 100,000 people | :06:36. | :06:42. | |
in the UK who have had facial paralysis for years. | :06:43. | :06:47. | |
So each one of these dots represents the position | :06:48. | :06:49. | |
And so, for example, if you were to try and do | :06:50. | :06:54. | |
And the darker the red, the bigger the signal. | :06:55. | :07:01. | |
So because my left side is better and stronger... | :07:02. | :07:04. | |
..it's showing up as stronger on the screen. | :07:05. | :07:07. | |
This is great because for the first time, I'm getting accurate | :07:08. | :07:15. | |
information about what is going on with my face. | :07:16. | :07:17. | |
I tend to overwork this side of my face, so this really | :07:18. | :07:23. | |
is giving me feedback that I have to dampen down the movements I don't | :07:24. | :07:27. | |
want, and this is just so good at doing that. | :07:28. | :07:32. | |
I sort of try and practise in front of a mirror. | :07:33. | :07:35. | |
It's not quite as subtle as this, is it? | :07:36. | :07:37. | |
And also, I'm not that keen on looking in mirrors, | :07:38. | :07:40. | |
This headset takes all the information from sensors, | :07:41. | :07:49. | |
just like in the goggles, but now translates it into real-time | :07:50. | :07:52. | |
Yeah, so I'm trying really hard to make her do a full smile... | :07:53. | :07:57. | |
Doing it to a mirror, you kind of tell yourself | :07:58. | :08:04. | |
Whereas she is like, oh, no, that's not what it looks like. | :08:05. | :08:23. | |
It might sound strange to say, but for the first time | :08:24. | :08:26. | |
since my accident, I'm able to see what my smile actually looks like. | :08:27. | :08:29. | |
Not to make it sound like, I dunno, a strange way, | :08:30. | :08:32. | |
but you're kind of doing it with somebody else. | :08:33. | :08:34. | |
My biggest aim for this would be to be able to help | :08:35. | :08:40. | |
That's been one of my aims for the last 30 years. | :08:41. | :08:55. | |
Have you heard the one about the alien who walks | :08:56. | :09:03. | |
Now, as impressive as this bizarre setup looks, | :09:04. | :09:10. | |
these motion-capture suits and stages are actually the standard | :09:11. | :09:12. | |
way that Industrial Light Magic uses actors to give realistic | :09:13. | :09:15. | |
movements to computer-generated principal characters. | :09:16. | :09:16. | |
No worries! You were very frightening. | :09:17. | :09:19. | |
I mean, he's a nice dad, I think, Jalien. | :09:20. | :09:25. | |
Even the fact that Jalien here is being rendered in real time | :09:26. | :09:28. | |
for the director to see during the performance is not | :09:29. | :09:30. | |
What is brand-new here is the live rendering | :09:31. | :09:38. | |
You know, our big focus was around the face and being able to capture | :09:39. | :09:46. | |
the face at the same time as the body. | :09:47. | :09:48. | |
And we can determine what expressions are happening each | :09:49. | :09:51. | |
frame, and then directors can see that live and make decisions | :09:52. | :09:54. | |
on if the character is working as a character, | :09:55. | :09:56. | |
whether his expressions need to change in terms of the model. | :09:57. | :09:59. | |
In order to process an actor's expressions quickly enough, | :10:00. | :10:04. | |
only one face cam and a few Mo-cap dots are used. | :10:05. | :10:12. | |
This simplified live data is then compared to a higher-resolution 3-D | :10:13. | :10:15. | |
capture of the actor's face that's taken beforehand on a rig called... | :10:16. | :10:18. | |
Now, unlike other facial-capture systems we've seen, which take | :10:19. | :10:25. | |
still images of the actor's face, here they're shooting video | :10:26. | :10:28. | |
of my face moving into and out of each emotion. | :10:29. | :10:32. | |
That means that the facial recreation and the animations | :10:33. | :10:34. | |
The live, high-quality rendering of both face and body can also | :10:35. | :10:45. | |
become a magic mirror on sets, to help the actor to get | :10:46. | :10:48. | |
And I guess it really does make you move differently when you're | :10:49. | :10:52. | |
on set, if you're playing a half-tonne alien, | :10:53. | :10:55. | |
It totally does, as long as I engage my imagination. | :10:56. | :10:59. | |
Because if you can see, I'm totally beautifully... | :11:00. | :11:01. | |
You know, in a way that Jalien can't, my wetsuit moves in a way | :11:02. | :11:09. | |
that maybe that arm and that outfit doesn't move. | :11:10. | :11:17. | |
It's good showing you my, er, my stuff. | :11:18. | :11:28. | |
Don't forget, we live on Facebook and on Twitter... | :11:29. | :11:32. | |
Thanks for having us at your place, Jalien. | :11:33. | :11:35. | |
Now, get out of here! Yeah. | :11:36. | :11:38. | |
Hmm... Out! | :11:39. | :11:39. |